Emotional agent : A modeling and an application

1. Emotional agent : A modeling and an application Khuloodet al. Information and Software Technology vol. 49, pp. 695-716, 2007 장수형

2. Introduction • Emotion • Essential part of human • Influence how we adapt, learn, behavior, communicate with others • Important and active role in the human decision-making process • Use artificial agent as test bed • Exploit some of the roles that emotions play in biological system • Develop mechanisms and tools to ground and enhance autonomy • Definition of emotion • Occurring when the cognitive, physiological, and motor/expressive components are usually more or less dissociated in serving separate functions • Psychological states

3. Introduction • The different affective states • Emotion • Angry, sad, joyful, fearful, ashamed, proud, elated, desperate • Mood • Cheerful, gloomy, irritable, listless, depressed, buoyant • Preferences/Attitudes • Liking, loving, hating, valuing, desiring • Emotion History • Psychology, Neurology, Philosophy, Cognitive science • ‘The Emotional Brain’ – LeDoux • Emotional process in the brain • Terms of desires and expectations

4. Emotion • Role of emotion in nature • Serve several crucial roles in animals and human alike • Provide a basic evaluation in terms of hedonic values • Cause the organism to be attracted to what it likes and to avoid what it does not like • Fear-anger system may generate fight or flight behavior • Influence direct cognitive process, process strategies • Play an important role in social contexts • Raging from signaling emotional state through facial expressions and gesture

5. Emotion • Role of emotions in artificial agents • Action selection • Adaptation • Social regulation • Sensory integration • Alarm mechanisms • Motivation • Goal management • Learning • Attention focus • Memory control • Strategic processing • Self-model

6. Emotion • Emotion cognitive appraisal • Complex , dynamic, varying both episodically and longitudinally • A negative event can trigger an emotional response • Dissipate within a short time

8. Emotion • OCC-model • Vague, vary, difficult to tell apart • A lot of confusion • Basic emotions, reduce everything • Consider the best categorization of emotion • World as divided in three different categories • Events, agents, objects • Categories down to five distinct positive and five negative

9. Emotional agent modeling • Symbolic approach one • Model the behavior of two agents and objects living in a simulated world • RIA(Regular Intelligent Agent), EIA(Emotional Intelligent Agent) • Same object • Main goal to achieve certain activities • Agent’s global variables and states can be monitored through the simulation using graph, plot, report

10. Emotional agent modeling • Model hypothesis • The mission ‘To bring life’ to several application • Information, transaction, education, tutoring, business, entertainment and e-commerce • Develop artificial mechanisms • Can play the role emotion plays in natural life • Artificial emotions • NetLogo • Extensions of the LOGO • Control many agent on the screen • http://ccl.northwestern.edu/netlogo. • An agent modeling environment • Well suited for modeling complex system • Hundreds or thousands of independent ‘agents’

11. Netlogo • System • Run on MacOS, Windows, Linux, et al. • Model can be saved as applets to be embedded in web • Language • Fully programmable • Simple language structure • Language is Logo • Unlimited number of agent and variable • Integer and double precision floating-point math • Runs are exactly reproducible cross platform • Environment • Graphics display supports turtle shapes and size, exact turtle positions, and turtle and patch label • Interface builder with buttons, sliders, switches, choices, monitors, and text boxes

12. Orphanage scenario • Require the develop of a Netlogo environment providing a set of behavior rules • Be used for the simulation of agent behavior • Emotional agent behavior toolkit • The Orphanage Care Problem • Two agents • To achieve agent’s main goal • Agent should go to Orphanage • Taking care of the Orphanage depends on the agent working capacity • Taking care of the Orphanage depends on the agent earning level

13. Orphanage scenario • To preserve earning level from decline to zero • Agent should go to work to make some money • Working capacity can be improved at the Academy • Agent should go to the Academy • Improve its knowledge, hence, earning salary • Agent must pay fee • Working capacity do not decay over time • Agent need to raise its social capacity • Agent should go a social place such as club, restaurant, mall, party • Going their need expense which costs money • Social capacity do not decay over time

14. Emotion on Orphanage • Important roles at the control-level of agents behavior • Lead a reflexive reaction • Support the goal and motivation of an agent • Can create new motivations • Operate a the lever of control of agent architecture • Behavior of the agent will improve • Agent can generate emotion signal, evaluate and assesses events • Integration of Agent Goal, Personality, behavior • Netlogo can be varying initial conditions

15. Agent attributes

16. Agent attributes • Agent attributes

17. Simulation of objects

18. The Orphanage • Job • Club • Academy • Main-Goal Status • Agent’s Performance Measure • Social capacity • Working capacity • Earning level • Make sure • Their orphanage status does not decay completely • They do not run out of money

19. General Concept

20. Agent goals • Main goal • Take care of the Orphanage and as good as they can • Sub goal

21. Emotions in the simulation model • Emotions come into play just after event perception • Compare to its goals and standards • Attitudes are also… • Result • Value of Event-based emotion, attribution emotions and attraction emotions • The appraisal/evaluation mechanism • OCC-theory • Rise to emotions • Less complex than the full human emotion spectrum • Play a meaningful role in the mental processes

22. Emotions in the simulation model • Emotion parameters • Event-based emotions • Be influenced by the level of Orphanage-Status, earning level, social, work capacity • Attribution emotions • Be affected by the measure of other agents(work, learn or socialize with) • Attraction emotions • Works the same as attribution emotion • With liking/disliking of object • Agent behavior • ‘Behaviors with perception’ concept • Depend upon the current state of environment(perception) • State of the world, other agent

23. RIA • Thinking process(RIA) • Receives its initial states of it memory, parameter • Perceive behavioral Environment • Goal filtering • Behavior/action

24. Perception(behavior environment scanning) • Scans the environment and gathers data about object features • Assign priorities to the goal action • The orphanage status level • The earning level • Perception rules • Checks money level and give certain priority for job

25. Reasoning(simple inference) • If there are two goal-actions with equal priority • Decide which action is important

26. Execution • With highest priority • Going-to-job, learning-at-academy, socialize-at-clue • Result can be noticed • Orphanage status level • Working/social capacity • Earning level

27. EIA • Thinking process(EIA) • Receive its initial states of its memory and other initial parameter • Perceive the behavioral environment • Appraisal for situation is performed • Emotion generation • Emotion normalization • Personality influence • Goal Filtering • Action

28. EIA • Evaluate agent’s attitudes

29. EIA

30. Simulation • Test • 2000 iteration of the simulation

31. Result • Run 10 times

32. Result

33. Result

34. conclusions • Artificial emotions can be used in different ways to influence decision-making • Orphanage Care Problem • Emotions can be successfully modeled in agent • Outperform it non-emotional counterpart • EIA can be used in decision making in dynamic system model

35. E.N.D