agents to simulate social human behaviour in a work team agents to simulate social human behaviour...
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Agents to Simulate Social Human Agents to Simulate Social Human Behaviour in a Work TeamBehaviour in a Work Team
Barcelona, February 2003.Barcelona, February 2003.
Arantza AldeaArantza Aldea
[email protected]@etse.urv.es
SSPAINPAIN
Research ActivitiesResearch Activities
Applications of AI to industry– Multi-Agent Systems– Ontology-Based Search & Information
Extraction– Model-Based Reasoning
Multi-Agent SystemsMulti-Agent Systems
Information Society – AgentCities
Simulation of work teams
Agents to simulate social behaviourAgents 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
IntroductionIntroduction
• 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.
Brief DescriptionBrief Description
Working teamselection
Group behavioursimulation
Best teamselection
Add/deleteindividuals
Workingteamcases Finish?
ProjectManager
Design problem
new working team
Proposed working team
working team
no
yes
Simulation of societies
The Model: General ArchitectureThe Model: General Architecture
The Team Simulation Process.
SocialStatus
Cognition
Perception
Behaviour Actor
Basic Architecture of PECS Agents. (Urban 2000)
Sensor
Emotion Physics
The Model: Agents ArchitectureThe Model: Agents Architecture
SocialStatus
Cognition
Perception
Behaviour Actor
PECS Modified Architecture.
Emotion / Personality
The Model: Agents ArchitectureThe Model: Agents Architecture
Cognition. Project Manager Chemical Engineer Technician Assistant
Creativity
Experience
Social Status.
Introverted / Extroverted Prefers to work in team / Prefers to work alone
Sociologists, psychologists.
Internal Parameters of the AgentsInternal Parameters of the Agents
}
Emotion / Personality. Desire } Frijda 1986 Interest Disgust Anxiety } Johnson-Laird 1992
Stress
Amiable Expressive Analytical Driver
S. Schubert, Leadership Connections Inc. 1997
} Izard 1991}
Personality TrendsPersonality Trends
Amiable.
Priority: RelationshipsSpeciality: Support; “We’re all in this together so let’s work as a team”
Expressive.
Priority: RelationshipsSpeciality: Socialising; “Let me tell what happened to me...”
Analytical.
Priority: The taskSpeciality: Processes; systems; “Can you provide documentation for your claims?”
Driver.
Priority: The taskSpeciality: Being in control; “I want it done right and I want it done now.”
BEGINTASK 1 TASK 2
TASK 3
TASK 4
TASK 5
TASK 6
TASK 7
TASK 8
...TASK N
END
Number of Participants
Duration
Sequence
Difficulty of the Task
Type of Task
Deadline
Priority
Cost
Quality
The Model: Tasks RepresentationThe Model: Tasks Representation
Differents organisation types will be tested:
S in Jera rq u ías
C en tra lizad aA rb o lTree Hierarchy
Centralised Hierarchy
Without Hierarchies
The Model: Organisation LevelThe Model: Organisation Level
The Model: Agent BehaviourThe Model: Agent Behaviour
2
2
2
)(
2
1)( s
mx
es
xf
m s
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
Three Dimensions to Evaluate a Team:Three Dimensions to Evaluate a Team:
Number of Members.
Agents with Different Characteristics.
Type of Organisations.
The Model: Team Evaluation The Model: Team Evaluation
Configuration Component
Team Configuration
Tasks Configuration
Simulation Component
Selection of Weight Agent Internal Parameters
Number of Simulations
Results Component
Show Team Behaviour
Graphical Statistics (future work)
The Prototype: Main ComponentsThe Prototype: Main Components
The Prototype: User InterfacesThe Prototype: User Interfaces
TasksConfiguration
Selection of Weight Agent Internal Parameters
Use of JADE 2.5Use of JADE 2.5
The Prototype: Initial ResultsThe Prototype: Initial Results
Team Members
1 Project Manager
3 Engineers
3 Technicians
3 Assistants
Example Configuration:Example Configuration:
Project
12 Different tasks
Number of simulations
100
Organisation
Centralised Hierarchy
The Prototype: Initial ResultsThe Prototype: Initial Results
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.
We observe that:We observe that:
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
Future WorkFuture Work
Things to do...Things to do...
At the end ...At the end ...
ConclusionsConclusions
Emotions, Personality, Stress
Different Organisation
Types
Social Characteristics
SimulationProcess
... help the project manager ... help the project manager to select the most suitable to select the most suitable team members for a team members for a specific project.specific project.