Models of multi-agent behavior: a simulation and Expert Environment approach

Thesis/Dissertation · Tue Jan 01 04:00:00 EST 1985

OSTI ID:5875002

Lounamaa, P H.M.

The goal of this thesis is to improve our understanding of behavioral phenomena in multi-agent decision making via modeling. A secondary goal is to develop a powerful simulation methodology for analyzing dynamic systems. A research question is the relevance of artificial intelligence techniques. A Simulation and Expert Environment (SEE), developed in LISP, integrates difference equation simulation with object-oriented programming and rule-based reasoning. The object-oriented approach offers a method for managing variants of the models. Ways to integrate rule-based reasoning and simulation are demonstrated, but the former's computational inefficiency limits usefulness. The system provides fast runaround between defining a model and obtaining results, which increases the productivity of the modeler, and encourages experimental modeling, leading to novel formulations and results. SEE is used to study the impact of biases, attribution heuristics, and trust on decision making in a team whose members are myopic and altruistic. The theme of this study is trust as a counter-bias. Using experimental modeling and the tools in SEE for exploring parametric solutions, behaviorally substantial results are obtained.

• Research Organization: Stanford Univ., CA (USA)
• OSTI ID: 5875002
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARTIFICIAL INTELLIGENCE
COMPUTERIZED SIMULATION
DECISION MAKING
MATHEMATICAL MODELS
PARAMETRIC ANALYSIS
PROGRAMMING
SIMULATION