EMO - A Computational Emotional State Module : Emotions and their influence on the behaviour of autonomous agents

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(1)Examensarbete LITH-ITN-MT-EX--07/032--SE. EMO - A Computational Emotional State Module. Emotions and their influence on the behaviour of autonomous agents Jimmy Esbjörnsson 2007-05-28. Department of Science and Technology Linköpings Universitet SE-601 74 Norrköping, Sweden. Institutionen för teknik och naturvetenskap Linköpings Universitet 601 74 Norrköping.

(2) LITH-ITN-MT-EX--07/032--SE. EMO - A Computational Emotional State Module. Emotions and their influence on the behaviour of autonomous agents Examensarbete utfört i medieteknik vid Linköpings Tekniska Högskola, Campus Norrköping. Jimmy Esbjörnsson Handledare Pierangelo Dell'Acqua Examinator Pierangelo Dell'Acqua Norrköping 2007-05-28.

(3) Datum Date. Avdelning, Institution Division, Department Institutionen för teknik och naturvetenskap. 2007-05-28. Department of Science and Technology. Språk Language. Rapporttyp Report category. Svenska/Swedish x Engelska/English. Examensarbete B-uppsats C-uppsats x D-uppsats. ISBN _____________________________________________________ ISRN LITH-ITN-MT-EX--07/032--SE _________________________________________________________________ Serietitel och serienummer ISSN Title of series, numbering ___________________________________. _ ________________ _ ________________. URL för elektronisk version. Titel Title. Författare Author. EMO - A Computational Emotional State Module. Emotions and their influence on the behaviour of autonomous agents. Jimmy Esbjörnsson. Sammanfattning Abstract Artificial. intelligence (AI) is already a fundamental component of computer games. In this context is emotions a growing part in simulating real life. The proposed emotional state module, provides a way for the game agents to select an action in real-time virtual environments. The modules function has been tested with the open-source strategy game ORTS. This thesis proposes a new approach for the design of an interacting network, similar to a spreading activation system (Maes, 1991), of emotional states that keeps track of emotion intensities changing and interacting over time. The network of emotions can represent any number of persisting states, such as moods, emotions and drives. Any emotional signal can affect every state positively or negatively. The states' response to emotional signals are influenced by the other states represented in the network. The network is contained within an emotional state module. This interactions between emotions are not the focus of much research, neither is the representation model. The focus tend to be on the mechanisms eliciting emotions and on how to express the emotions.. Nyckelord Keyword. artificial intelligence (AI), emotions, feelings, mood, sigmoid function, response curve, behaviour, autonomous agents, real-time strategy game (RTS), open real-time strategy (0RTS).

(4) Upphovsrätt Detta dokument hålls tillgängligt på Internet – eller dess framtida ersättare – under en längre tid från publiceringsdatum under förutsättning att inga extraordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Överföring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och tillgängligheten finns det lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/ Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a considerable time from the date of publication barring exceptional circumstances. The online availability of the document implies a permanent permission for anyone to read, to download, to print out single copies for your own use and to use it unchanged for any non-commercial research and educational purpose. Subsequent transfers of copyright cannot revoke this permission. All other uses of the document are conditional on the consent of the copyright owner. The publisher has taken technical and administrative measures to assure authenticity, security and accessibility. According to intellectual property law the author has the right to be mentioned when his/her work is accessed as described above and to be protected against infringement. For additional information about the Linköping University Electronic Press and its procedures for publication and for assurance of document integrity, please refer to its WWW home page: http://www.ep.liu.se/. © Jimmy Esbjörnsson.

(5) EMO A Computational Emotional State Module Emotions and their influence on the behaviour of autonomous agents. Jimmy Esbjörnsson VITA Visual Information Technology and Applications Linköping University jimstein3d@yahoo.se.

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(7) Abstract Artificial intelligence (AI) is already a fundamental component of computer games. In this context is emotions a growing part in simulating real life. The proposed emotional state module, provides a way for the game agents to select an action in realtime virtual environments. The modules function has been tested with the opensource strategy game ORTS. Extensive research work on the subject of emotions is available in literature, and different models of emotional systems are debated. The material have been reviewed the material and a model have been constructed based on psychological studies by Picard, Minsky, Pinker and others. Especially the work of Picard has been very influential. This thesis proposes a new approach for the design of an interacting network, similar to a spreading activation system (Maes, 1991), of emotional states that keeps track of emotion intensities changing and interacting over time. The network of emotions can represent any number of persisting states, such as moods, emotions and drives. Any emotional signal can affect every state positively or negatively. The states' response to emotional signals are influenced by the other states represented in the network. The network is contained within an emotional state module. This interactions between emotions are not the focus of much research, neither is the representation model. The focus tend to be on the mechanisms eliciting emotions and on how to express the emotions. Key words: artificial intelligence (AI), emotions, feelings, mood, sigmoid function, response curve, behaviour, autonomous agents, realtime strategy game (RTS), open realtime strategy (ORTS).

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(9) Table of Contents Glossary................................................................................................................................. ....................1 1 Introduction......................................................................................................................................... ...3 1.1 Preface......................................................................................................................... ...................3 1.2 Audience......................................................................................................................................... 4 1.3 Overview and Goals............................................................................................................... ........4 1.4 Achievements.............................................................................................................. ...................4 1.5 Acknowledgements................................................................................................. .......................5 2 The Concept of Emotions .......................................................................................................... ...........7 2.1 A brain to simulate................................................................................................................. ........7 2.2 Emotional genes....................................................................................................................... ......8 2.3 The purpose of emotions................................................................................ .............................11 2.4 Why machines need emotions.......................................................................... ...........................14 2.5 The classification of emotions and feelings................................................................................16 2.6 Basic Emotions................................................................................................ ............................17 2.7 Appraisal Theory............................................................................................... ..........................18 The OCC Model......................................................................................................... ...............19 The Roseman Model....................................................................................... ..........................19 2.8 Temperament and Mood................................................................................................ ..............20 2.9 Models with Multiple Emotion Layers................................................................................ ........21 3 Architecture............................................................................................................. ............................23 3.1 A model to build on.............................................................................................. .......................23 3.2 The Emotional State Module............................................................................................... ........24 Signal representation for emotions............................................................................ ....................27 Mood of an emotional state.................................................................................. .........................30 Considerations..................................................................................................................... ...........31 3.3 The Decision Making Module....................................................................................... ..............31 3.4 EMO Integrated with ORTS through a middleware...................................................................32 3.5 Configuration.................................................................................................................... ...........35 4 Contribution, Future Work and Conclusions....................................................................................... 37 4.1 Contribution............................................................................................................ .....................37 4.2 Future Work........................................................................................................ .........................37 4.3 Related work........................................................................................................... .....................38 Appraisal models...................................................................................................................... .38 The eliciting emotion model....................................................................................... ..............38 The project Oz model............................................................................................................. ...39 The Carthxis model.............................................................................................................. .....39 The DER model............................................................................................ ............................40 4.4 Conclusion .............................................................................................................. ....................40 5 References.................................................................................................................................. ..........43 6 Appendix.......................................................................................................................................... ....45.

(10) A)The ORTS Project.................................................................................................... ...........................45 A.1 Background............................................................................................... .............................45 A.2 Getting started....................................................................................................... .................47 A.3 Brief overview of ORTS..................................................................................... ...................49 B)The Brain...................................................................................................................... .......................55.

(11) Glossary The content of this glossary section is given as a guidance for you to understand the findings in this thesis. Affect is the scientific term used to describe an agent's externally displayed mood. This term doesn’t regard at what point an emotion becomes "genuine" to the agent. (Affect is also a verb meaning “have an influence on”, often confused with the word effect.) Affective The word affective is sometimes used as an opposite to cognitive. But the word simply means “having to do with emotions“. Agent is an intelligent actor, which observe and act upon an environment, real or virtual. An agent is specified in terms of a set of capabilities (see actions), knowledge (see beliefs), ambitions (see desires) and commitments (see goals). Amygdala See appendix B. Appraisal is the act of estimating the value of a perceived sensation. Beliefs are the agents understanding about the current state of the environment. Cognitive refers to the mind's processing of information, applying knowledge and changing preferences. Cortex See appendix B. Desires are the ambitions related to personal standard (see personal standard) and aspirations. No universal desires exists – every agent can have a unique set of ambitions. Emotion is a term that has no single universally accepted definition. Some authors define emotion as an intense state arising autonomically in the nervous system rather than through conscious effort, other define emotion as a cognitive process requiring a conscious effort. In this thesis is the term emotion used mostly to refer to unconscious processes, but the term is sometimes also including feelings when the usefulness of separating the two are vague. Feelings are affective states of consciousness. Conscious feelings are states of consciousness and thus perceptions of an underlying brain activity. Feeling is a cognitive function, meaning we are making emotional judgements; feeling evaluates. Goals are the things the agent is committed to achieve. Hypothalamus See appendix B. Hippocampus See appendix B. Limbic system See appendix B. Mood is a relatively lasting emotional or affective state. Moods differ from emotions in moods are less specific, often less intense, less likely to be triggered by a particular stimulus or event and last 1.

(12) longer. Mood is a function of the complete set of emotions that constitutes someone's mental state at a particular time. Needs are the universally shared physiological and psychological requirements for the well being of all agents. Every need is expressed in several different personal desires. Neocortex See appendix B. Neuroendocrine cells are a specialized group of nerve cells (neurons) that produce hormones. Personal Standards is the standards of good conduct and high morals that must prevail over the temptations of deceit and immorality. Rcomplex See appendix B. Sensation as used in this thesis refers to a noncognitive evaluative sensation by appraisal that may or may not register in consciousness. Timeinvariant system is one whose output does not depend explicitly on time. Timevariant system is one whose output as explicit dependence on time. Triune brain See appendix B. Thalamus See appendix B.. 2.

(13) 1 Introduction “What are emotions? Emotions are the glue that holds the cells of the organism together in the material world, and in the spiritual world they're the glue that holds the classrooms and the society together. That's why they are so interesting, because they're on a material level – the molecules of emotion as I've studied them as a scientist – and they're in the spiritual realm as well.” – Candace Pert, EQ Today.. 1.1 Preface Artificial intelligence (AI) is already a fundamental component of computer games. At the surface level what the player notice is the computer graphics, and therefore business people in game industry do care a whole lot about new graphics FX that can help in their sales pitch. For some time little have been emphasised on the artificial intelligence advances. The reason is that it is something the consumer will notice only while playing the game and nothing one is used to consider before buying the actual game, but it has great potentials to become the new focus of the industry after the steam of computer graphics has gone out and the benefits of each new generation graphic board becomes less obvious. There is a difference between scientific AI and game AI but the trend is to bring more and more from the scientific world unto games. In this context is emotions a growing part in simulating real life. While I was working on this thesis I started to see more interesting things happening in the realtimes strategy (RTS) game domain than in any other area of artificial intelligence in games. In “Company of Heroes” and “Face of War” I saw AI that really reacts to the situation and provides a sense of chaos. We can expect to see more games where each unit even will have a unique personality and may not always follow orders. We will see more games with agents that asses the situation dynamically and react realistically without being scripted to react in a predefined way, where every agent must be managed and cared for because each unit is of a certain personality type. We have already seen previous attempts to achieve this but they have been limited and not very successful because the dominating approach used was to script AI. The problem currently facing the introduction of a strong AI is to the balance the control between what the player expects will be carried out and the freedom of the AI brain of agents. The AI trait currently just gets in the way of the user as the AI will do things like force the agent to drop to a crawl or stop and return enemy fire when the player is trying to get him to sprint to safety. Sometimes the agent won't respond to movement commands just because the AI is not up for this type of obedience at the moment. The benefits that emotions can bring to the artificial domain are promising but also a lot of confusion will come with it. What is an emotion? To start with we have a complex array of overlapping words in our language to describe them, and we have probably more than a hundred definitions from scientist of emotions to choose from. I picked this topic for my diploma work not only for my interest in games but mostly for my interest in psychology and Neurolinguistic programming (NLP). This topic has given me the possibility to dig 3.

(14) into numerous books and articles that I would not have cared for otherwise.. 1.2 Audience My primary intended audience for this thesis are post graduates or students in upperlevel under graduate computer classes. This thesis assumes a knowledge of artificial intelligence at university level as well as a robust practice in programming and design patterns. Some knowledge of psychology will be beneficial, although certain key concepts will be reviewed here. The secondary audience is researchers and students interested in writing their own software agents. Although many of the concepts in this thesis are familiar to experienced people I believe that the appendix section covering ORTS will be of particular interest for those that want to get started developing their own AI in realtimestrategy (RTS) games.. 1.3 Overview and Goals The hypothesis behind this thesis was that I would be able to express an emotional state of the agent that can influence them to make healthy decisions about what behaviour to perform, and that this may increase the believability of a RTS game agents. This hypothesis led to two goals: The primary goal and focus have been that of the construction of a computational module that can handle emotional stimuli in a novel way by using parametric signals representing sensations. The secondary goal has been to interface the emotional state module with ORTS, an open source programming environment for RTS games, so that the module could be evaluated in a real time system. The ORTS is such an environment it aspires to not lack the key features found in highquality RTS games. As a side benefit, I found results from my research that strongly indicate that there are in reality no pure rational thoughts in humans, instead every thought is influenced by emotions. . 1.4 Achievements The model of this thesis extends an appraisal mechanism, such as the OCC model (Ortony et al., 1988), that classifies events, actions and objects, and outputs emotional states. The output of the appraisal is instead define as an emotional signal. Emotional signals are defined by the name of the emotional state, its intensity value and the three durations phases. Each signal has the characteristic phases of an attack, sustain and decay phase. Each signal is then processed through a number of filter patterns that modifies the signal according to the personality and current state of the agent. . 4.

(15) The main achievements of this thesis are: ●. a timevariant emotional response through dynamic thresholds. ●. a method for composing of emotional states. ●. a network of interacting emotional states with both inhibitory and excitatory influence. ●. ●. a saturation levels for each emotional response, meaning they can not reach extreme heights or depths a method to accumulate emotional response over time. 1.5 Acknowledgements First of all I would like to thank the ORTS people, especially to Timothy Furtak, for the updates and fixes they did when it was asked for. Pierangelo Dell Acqua, head of the AICG lab at ITN, has contributed to this thesis in many ways, without his support and guideline would the end result of this thesis not have reached its current level. He contributed with office space and good equipment to work with. His tireless input of new ideas and questions was both challenging and leading to new insights. Anja Johansson were instrumental in making the office space such a nice place to work in, she contributed with a nice atmosphere and many good dialogues, as well as for using and testing my implementation and giving feedback on my report. I am especially grateful to Emma Mattsson, my soulmate, for her unfailing encouragement, love, support, and patience with my work obsession. This thesis is dedicated to her and to my parents who gave me all the support I needed to get here in the first place. . 5.

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(17) 2 The Concept of Emotions “What are emotions? Emotions are human beings' warning systems as to what is really going on around them. Emotions are our most reliable indicators of how things are going in our lives. They are also like an internal gyroscope; emotions help keep us on the right track by making sure that we are led by more than cognition” – Maurice Elias, EQ Today. This chapter will highlight samples from the historical development of emotional studies and toward today's cognitive and affective research. . 2.1 A brain to simulate The computational theory of the mind originates from the mathematician Allan Turing (19121954). His assertion was that the computer, when properly programmed, could rival the human brain. It founded the computer science and artificial intelligence of coming decades. Turing used the body mind interaction theory that believes are interpretations about the surrounding environment, incarnated as symbols in the mind. This is well illustrated by a quotation from the psychologist George Miller: "The crowning intellectual accomplishment of the brain is the real world. All the fundamental aspects of the real world of our experiences are adaptive interpretations of the really real world of physics." The symbols are the physical states of neurons or digital switches which symbolise things in the world, triggered by our senses. The symbols can also represent what they can do once they are triggered. The mathematical use of symbols came from Boole (18151864), that lead to a greater understanding of assumption grammar (the assumption that language is founded on logic). The use of symbols allow us to imagine that the mind combines one symbol representing one belief with another symbol representation another belief and this then can (if the logic holds true) give rise to a new symbol, representing yet another belief. This has led to the development of logic programming techniques, for example Prolog and later XSB. But how does the mind really work? MIT/Howard professor Dr. Steven Pinker (1954 ) summed it up in five words during a TVshow interview1: “Brain cells fires in patterns.” And he explained further that: “One pattern correspond to one thought, one pattern cause another pattern, and that is what happens when we think.” The symbols are the abstract representation of these patterns. Pinker belong to the supporters of the evolutionary psychology that was more or less crystallised by Tooby & Cosmides (Barkow et al., 1995; Pinker 1997) but had already had some predecessors like Plutchik (19272006). “Emotions”, Plutchik says, “are best observed through an evolutionary perspective as adaptations triggered by the challenges of survival and reproduction that are part of every organism’s existence.” An evolutionary approach, Plutchik argues, can sort out the roles of emotion, impulse and action and, in a therapeutic setting, help people understand the circumstances in which emotions can sometimes fail in their adaptive tasks: for example, when one change the light bulb it doesn't help to have fear of heights. Evolutionary psychology has been labeled by Pinker as the new science of the 1 “The Colbert Report” http://www.comedycentral.com/shows/the_colbert_report/videos/celebrity_interviews/index.jhtml 7.

(18) human nature. The theory has a radical vision of cognition as a “bag of tricks” rather than a neat integrated system. This theory is gaining support from robotics (Clark, 2001) because it promises a way to generate adaptive behaviour in realtime. The theory encourages abandoning the use of an inner store of symbols, the unified knowledge base (common in artificial intelligence models) in favour of a more neurologically realistic version. This version consists of multiple representation types, local memory banks and letting components, cognitive subsystems, that communicate in a wide range of different ways, processing operations in parallel. Thinking is information processing or computation, but comparing it to the way a computer is operating is not so simple even if the thinking stuff that goes in to be processed would be the same. The problem is also that you would explain things you don't understand in the human mind world with equivalents from the computer world, and this is apparently not avoided in the science literature. To describe and understand the mind, we need to be less focused on silicon circuits. The difference to mark out for starter is that neurons are great for pattern matching; the silicon chips are not. Computers work in serial — doing one thing at a time; brains work in parallel — doing millions of things at once (Pinker, 1997). Of course today there is a whole new breed of microprocessors with multiple cores causing a cultural chock among developers (New Scientist 2594). Sony's PS3 have IBM's nine core processors and Intel has presented a prototype of a general purpose processor equipped with 80 cores. But adding more cores to the chip is only half the battle, the second half of the battle is to figure out how to program it to divide the labour because the computers still work serial. The tasks must be divided up in a logical way and data from each operation combined at appropriate times. The simple way is to avoid the problem and run applications separately on the different cores. Only few tasks lend themselves well to parallel computer processing; like fluid dynamics and computer graphics rendering. But the most important difference between the human mind and the computers is that symbols in the form of sensations in the brain can't be stored (what we know of) but symbols in the form of cybernetic information can be stored.. 2.2 Emotional genes Evolutionary Psychology brings together two scientific revelations: one is the cognitive revelation of the 1950's and the 1960's, which explains the mechanics behind thought and emotions in terms of information and computation. Cognition is just a fancy word for the science that studies how the mind process perceptions, remembers and thinks. The other revelation is that of evolutionary biology from the 1960's and 1970's with explains the complex adaptive design of living entities in terms of Darwin and Wallace theories on the natural selection. Combine the two give a good toolkit; cognitive science helps us understand how a mind is possible and what kind of mind we have. Evolutionary biology helps understand why we have the kind of mind that we have. The theory proposes that many assumptions of the real world are built in by the natural selection, working by making good guesses on an incompletely described problem, stipulating that the mind is not quite as a general problem solver as we have come to believe. An example of such an inbuilt assumption is the visual system. Evolutionary Psychology is therefore an extension of biology with a narrow focus on the mind. This evolution has worked its way by sloppy copying what already exist. We can assume that the 8.

(19) language of thoughts is a result of evolution. Inherited braincircuits have given us the ability to reason about space and force, during evolution were these circuits separated from the eyes and muscles and references to the physical world were reduced to mere symbols, symbols that can represent more abstract concerns, like states, possessions, ideas and desires. The circuits have maintainted their computational capabilities and can reason about states being in one state at a time, shifting from one state to another and overcoming entities with the opposite valence; which make us able to reckon things about the traffic lights or to understand the cause of effects to manipulated objects; that a peeled banana was originally an uneaten banana. Even a chimpanzee understands what effect an eraser will have on a written page of text. But we are not only able to reason about our own bodily state but also to reason about other people's state. It is hard to read other people's minds even if we can make very good guesses from what they say, what is shown in their faces and what can be drawn from their behaviour, and be found out by looking at people's eyes. Even small toddlers are excellent mind readers of the language of thought; exceptionally bad at understanding the language of thoughts is those suffering from autism disorder. Facial expressions are useful in the process of thought reading because they are hard to fake. One could say that our emotions are "handcuffed" to the body because they grew out of evolutionary predecessors that were modern emotions may exploit the involuntariness of older reflexes, like phobias; a snake is always scary to apes and toddlers, but a gun is not. There is an apparent firewall in 20thcentury literature between emotion – described as something bodily (irrational impulses of violence and passion), versus reason – described as the intellect living in the mind working as a cool deliberator following the interests of self and society by keeping the emotions at check. The left brain versus the right brain or as the reptilian brain (i.e. the limbic system) – that would be responsible for feeding, fighting, fleeing and the sexual behaviour versus the Cerebral cortex – the prehistoric baggage and the intelligence that propelled us from the animals. This is a whole mountain of “crap” talk since no part of the nerve system is left untouched by the evolution, and we can't be condemned from the start not to be able to feel anything more than what our remote ancestors were able to feel. The concept of theories such as Neurolinguistic programming (NLP) claims that the emotions are easy to reprogram. NLP has a very pragmatic approach, applied to focus on mental excellence and how to reproduce it by changing believes using words and behavior. Richard Bandler, the coinventor (with John Grinder) of NLP, notes that the act of just laughing will alter the state of consciousness by releasing chemicals into your blood. The hallmark of NLP is summed up by the following quotation from Henry Ford: "Whether you believe you can, or you can't, you are right." Very influential for NLP is Noam Chomsky, who with the “Syntatic Structures” (1957) sparked the belief in a cognitive subsystems in psychology.. 9.

(20) The emotional repertoire varies widely even within a single species; for example dog breeds. even if the many visually distinguishable breeds are no older than two hundred years was dogs developed for enhancing behavioural traits already several millenniums ago, shown by a greater divergence in three different brain regions – frontal lobe, amygdala and hypothalamus, compared to wolves. It was evolutionarily beneficial for dogs to be exceptionally good at reading human signals, allowing (Björnerfeldt, 2007). Within the narrow gene poll of chimpanzees are the anatomical differences between Common and Bonobos Chimpanzees slight, but in sexual and social behaviour there are marked differences. The Common Chimpanzee is more of a warmonger than the Bonobos that is more of a nature's version of a peaceloving hippie. An even smaller gene poll is that of the humans, the differences between visually distinguishable groups are merely visual; any other distinguishable traits in behaviour can often be related to cultural backgrounds. All species show a genetic difference but the humans have small variations compared to other spices, for example there is more genetic difference between two Chimpanzees in the same forest than between two humans from different continents. (Pinker, 2002; Weber, 2006). Some parts of the human genome show a shallow and recent ancestry, but parts of it show a very deep ancestry. Something very uniquely happened to the human genome 40,000 years ago (New Scientist 2593), a mutation or perhaps reintegration of genes from our archaic sister species2 into the Homo Sapiens; the new genes were propelled by the natural selection and made the human race very successful in the cognitive adaptation. The cognitive adaptation means that adoption can happen in realtime instead of the need for natural evolution to promote the fittest design. The human species excellence in the cognitive adaptation give them an obvious advantage over other spices; allowing them to manipulate the environment to their benefits by social cooperation among nonkin leveraged by using a language for transferring knowledge symbols; especially humans unique way of referring to symbols independent of their current emotional state and ambitions. The tradeoff that the humans have done for this excellence is to be the only mammal that can't drink and breath at the same time, and to spend a disproportional long time in childhood because the human adaptation is not primarily “fur adaptation” but “knowhow adaptation." These three parts of the human excellence is called the cognitive niche theory and is well depicted in the Devil's Dictionary by Ambrose Bierce (1911): “MAN, noun. An animal so lost in rapturous contemplation of what he thinks he is as to overlook 2 Neanderthal (in Middle East and Europe, until 30,000? years ago) and Homo Erectus (on Java, Indonesia, until 25,000? years ago) in particular are interbreeding candidates, but there are also Homo Floresiensis (on Flores island, Indonesia, until 12,000 years ago) to be considered. These three spices along with Homo Sapiens was the only hominid groups that came through a bottleneck 73,000 to 63,000 years ago (Weber, 2006). 10.

(21) what he indubitably ought to be. His chief occupation is extermination of other animals and his own species, which, however, multiplies with such insistent rapidity as to infest the whole habitable earth and Canada.”. Still there are lesser variations that make each human unique in appearance, skills and interests, and in physiology and biochemistry. Some of the genetic differences affect the way we react to drugs. Some tremendously beneficial drugs are ineffective, or even dangerous, in some people. In turn, our mental configuration comes from our genetic program, but there is not a gene for every trait or anything suggesting that learning is unimportant, but evolutionary psychology gives a good motivation for why all humans would share universal needs and psychology, that would limit the possibly variation of cultures. The behavioural differences that are associated with distinct groups of people would be a result of them spending an extended time in childhood learning the nuances of the surrounding culture. With culture we associate locally accumulated expertise, customs and social arrangements.. 2.3 The purpose of emotions Evolution has been free to modify the emotional behaviour. Behaviour that is similar over many spices has been preserved because they are well adapted for all spices. The emotion fear triggers an acute stress response that makes the body ready to quickly react. Blood is redirected from the stomach and skin living butterflies and itchiness, and instead sent to the muscles. Rapid breathing takes in oxygen. Adrenalin releases fuel from the liver and help the blood declot. Plutchik (1989) claimed that “Cognition has developed in purpose to serve the emotions”, by which he means that cognitive processes help the individual predict emotional outcomes in the future to its behaviour, especially if behaviour is related to habitat selection. This correlation guarantees that the behaviour is relevant. But emotions are not the animal legacy of the lower levels of the triune brain (Pinker, 1997). According to the computational theory of the mindbody is the lifeblood of the psyche information and not foremost energy, and the emotions are designed to duplicate our genes and not to make us happy or morally wiser. An emotional program working at it is best would absolutely be able to verdict behaviour that is harmful to society or a self dilution. The cerebral cortex does not fight to control any reptilian brain, even if literature is littered with such examples, but instead the cerebral cortex works in tandem with emotional modules. Emotions are indispensable functions to the whole mind. This is not saying that evolution has had the time to adapt us to a modern life style. This can be exemplified with this lovely citation from the T.V. series “The Scrubs” by the character Dr. Cox: "I've been trained for many years to take any emotion I feel, push it down, and then let it out by drinking way too much and by yelling at the football players on my T.V. screen. And I...I really thought I hit the jackpot when I finally met a woman who was as disturbed and closedoff as I am”. Neurosciences place these emotional modules that colourize our experience in the Amygdala, a small oval shape in each temporal lobe. Amygdala receives signals from all lobes of the hippocampus, and cingulate gyrus, the brain steam as well as the cerebral cortex. Almost all the sensory information is delivered to a particular nuclear called basolateral nuclei in amygdala (Dariush, 2001). 11.

(22) All sense signals, like the sight of a snake, are first sent to the thalamus where a preliminary screening takes place. The main processing is carried out in the cortex where each of the senses is assigned a certain area. In the case that an emotional reaction (due to a cognition process) is called for, a message is sent to the amygdala. A breakthrough in the research occurred when it was found by measurements that a smaller part of the sense signal was also sent through a more direct and faster channel from thalamus to amygdala. The Amygdala in turn sends the signal to almost every part of the brain, including the decision making circuit in the frontal lobes. Damage on the Amygdala is reported causing flattening emotions, reduced fear and absence of hesitation (LeDoux, 1996 ).. Illustration based on LeDoux JE (1994) Emotion, Memory, and the Brain. Scientific American.. A historical point is that Charles Darwin (1899) in person should once have tested this automatic response in an experiment. He visited a zoo and placed his face against the thick glass window of the puff adder's cage, and tried to ignore the inevitable strike against the glass. However, when it came attacking, Darwin found that he had jumped one meter back from the glass. Amygdala's coloration, is a sort of colour coded marker that is put on the event to tell the importance of it. According to Dames (1995) does this somatic marker connect an event to a “gut” reaction that lead to aversion if the events were a failure, attraction if the events were a success. The marker is the emotional tone, the trace of the event, and connects it to a reaction. Even non bodily events like imagination can activate this emotional tone, and therefore also the reaction. Bower's comprehensive survey from 1981 of his network model (Dariush, 2001) talked about the mood congruence effect, he stated that the emotional state becomes a part of the experience, and in a particular emotional state it is easier to remember the experience that corresponds to this state. The philosopher Francis Bacon (15611626), famous of his uttering "Anger makes dull men witty, but it keeps them poor", and also Eric Eich in his survey from 1980 have similar reasoning's, describing state dependent recollections (Dariush, 2001). An example of such recollection would be that one thinks about how lovely it would 12.

(23) be to eat one's fill and then one would remember all the places one have found food before, and this would explain why some people would think of the McDonald instead of an expensive China Restaurant in a time of desperate need for food. Evolution has been programmed in deliberately because only if the emotions are in control it can help to connive intricate plots for escape, revenge, ambition and courtship. As a demonstration that emotions sharpen the mind I gives you the following citation from Winston Churchill observations: "There's no more exhilarating feeling than being shot at without result", a mind focusing experience many of us share. A computer runs a program by executing a list of instructions until it runs out of instructions. Living entities need a more flexible method of controlling execution. Intelligence is the pursuit of goals in the face of obstacles. Without goals the concept of intelligence is meaningless, each goal is archived by completing sub goals. If our emotional reactions to an urgent goal were “successful” we would be likely to remember the procedure by which we got out of it or into it. We are also likely to remember a new long term goal, which of staying out of the hazard in the first place, triggered by the sensation of relief. To support an augment against emotions, it would be interesting to study a mind operating presumably without them. A well known example of such a mind would be the one of the character Spock, the Vulcan from the Star Trek series. He is stipulated to lack all emotions except the “Pon farr” (a term for the Vulcan mating cycle, every seven year the adult Vulcan undergoes an extreme and erratic physical and psychological imbalance to make them carry out the mating ritual). But Vulcan's dominating feature, emotionlessness is only portrayed as letting him be in control and not losing his head in stressed situations. If he had no feelings why would he then be interested in exploring strange worlds and seek out new civilisations and “boldly go where no one has gone before”? Something must drive him. A good guess would be out of intellectual curiosity, an ambition to find and solve problems and solidarity with other allies. What would Spock do if he were faced with an attacking alien? He would probably take avoiding precaution because he fear being hurt (Pinker, 1997). If we agree that emotions are a cognitive function we can say that Spock lacks feelings, like those suffering Alexithymia3, but still have emotions. In fact, the actor William Shatner playing the role as 3 Alexithymia is a term coined to describe people who appeared to have deficiencies in understanding, processing, or describing their emotions. Research indicates that alexithymia overlaps with Asperger's syndrome. Studies have confirmed that 85% of people with ASD's (or Autism Spectrum Disorder) have alexithymia. This information was taken from Wikepedia (http://en.wikipedia.org/) 13.

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