Agents to Simulate Social Human Behaviour in a Work Team

1. SPAIN Agents to Simulate Social Human Behaviour in a Work Team Arantza Aldea aaldea@etse.urv.es Barcelona, February 2003.

2. Research Activities • Applications of AI to industry • Multi-Agent Systems • Ontology-Based Search & Information Extraction • Model-Based Reasoning

3. Multi-Agent Systems • Information Society • AgentCities • Simulation of work teams

4. Agents to simulate social behaviour • Introduction:Team Configuration • The Model: • General Architecture • Internal Architecture of the Agents. • Tasks Representation • Organisation Level • The Prototype • Future Work • Conclusions

5. Introduction Brief Description • In any complex project that requires several people working together, the configuration of the best possible team within the working constraints, is a difficult task(Biegler et al. 1997). • Intelligent Multi-Agent Systems can be used to simulate the human behaviour: • Emotions and Personality • Sociability • Groups Organisation • Case Study: selection of people to integrate a team in charge of the conceptual design of a chemical process.

6. The Model: General Architecture The Team Simulation Process.

7. The Model: Agents Architecture Perception Sensor Social Status Cognition Emotion Physics Behaviour Actor Basic Architecture of PECS Agents. (Urban 2000)

8. The Model: Agents Architecture Perception Social Status Cognition Emotion / Personality Behaviour Actor PECS Modified Architecture.

9. Social Status. • Introverted / Extroverted • Prefers to work in team / Prefers to work alone Sociologists, psychologists. Cognition. Emotion / Personality. • Project Manager • Chemical Engineer • Technician • Assistant } • Desire } Frijda 1986 • Interest • Disgust • Anxiety } Johnson-Laird 1992 • Stress • Creativity • Experience • Amiable • Expressive • Analytical • Driver S. Schubert, Leadership Connections Inc. 1997 } Izard 1991 Internal Parameters of the Agents }

10. Personality Trends Amiable. Priority: Relationships Speciality: Support; “We’re all in this together so let’s work as a team” Expressive. Priority: Relationships Speciality: Socialising; “Let me tell what happened to me...” Driver. Priority: The task Speciality: Being in control; “I want it done right and I want it done now.” Analytical. Priority: The task Speciality: Processes; systems; “Can you provide documentation for your claims?”

11. BEGIN END ... TASK N TASK 1 TASK 2 TASK 3 TASK 4 TASK 5 TASK 6 TASK 7 TASK 8 The Model: Tasks Representation • Number of Participants • Duration • Sequence • Difficulty of the Task • Type of Task • Deadline • Priority • Cost • Quality

12. The Model: Organisation Level Differents organisation types will be tested: Centralised Hierarchy Tree Hierarchy Without Hierarchies

13. m s The Model: Agent Behaviour The agent behaviour emerges by evaluating values of its internal properties, randomly modified around the initial values of each of the properties. Normal distribution with mean m(internal value of the agent, e.g. stress, interest, etc.) and standard deviation s These random variations are due to the non-deterministic nature of human behaviour

14. The Model: Team Evaluation Three Dimensions to Evaluate a Team: • Number of Members. • Agents with Different Characteristics. • Type of Organisations.

15. Simulation Component • Selection of Weight Agent Internal Parameters • Number of Simulations The Prototype: Main Components Configuration Component • Team Configuration • Tasks Configuration Results Component • Show Team Behaviour • Graphical Statistics (future work)

16. The Prototype: User Interfaces Use of JADE 2.5 Selection of Weight Agent Internal Parameters Tasks Configuration

17. The Prototype: Initial Results Example Configuration: Team Members Project • 1 Project Manager • 3 Engineers • 3 Technicians • 3 Assistants • 12 Different tasks Organisation • Centralised Hierarchy Number of simulations • 100

18. The Prototype: Initial Results We observe that: • Agents with high stress and in charge of a specialised task were the agents with more failures • Decreasing the stress parameter and executing the same number of simulations, the number of failures also decreased • Agents with an amiable personality and working in a task by themselves had more failures than successes • The most successful agents contains a high experience and analytical personality. • The creativity parameter only increases the number of successes when the agent is in charge of specialised tasks.

19. Future Work Things to do... • We are evaluating Fuzzy Logic to improve the agents behaviour. • More studies at organisation level: social characteristics, co-ordination, re-organisation, etc. • Implementation of other types of team co-ordination: tree hierarchical organisation, and no hierarchy • Validate the experimental results by comparing them with human teams • Unexpected events: how external factors affect the team behaviour

20. Different Organisation Types Emotions, Personality, Stress Social Characteristics Simulation Process Conclusions At the end ... ... help the project manager to select the most suitable team members for a specific project.