Wayne Iba

IJCAI Conference 2011 Conference Paper

Modeling the Emergence and Convergence of Norms

• Logan Brooks
• Wayne Iba
• Sandip Sen

In many multi-agent systems, the emergence of norms is the primary factor that determines overall behavior and utility. Agent simulations can be used to predict and study the development of these norms. However, a large number of simulations is usually required to provide an accurate depiction of the agents' behavior, and some rare contingencies may still be overlooked completely. The cost and risk involvedwith agent simulations can be reduced by analyzing a system theoretically and producing models of its behavior. We use such a theoretical approach to examine the dynamics of a population of agents playing a coordination game to determine all the norms to which the society can converge, and develop a system of linear recurrence relations that predict how frequently each of these norms will be reached, as well as the average convergence time. This analysis produces certain guarantees about system behavior that canot be provided by a purely empirical approach, and can be used to make predictions about the emergence of norms that numerically match those obtained through large-scale simulations.

AAMAS Conference 2011 Conference Paper

Modeling the Emergence of Norms

• Logan Brooks
• Wayne Iba
• Sandip Sen

Norms or conventions can be used as external correlating signals to promote coordination between rational agents and hence have merited in-depth study of the evolution and economics of norms both in the social sciences and in multi-agent systems. While agent simulations can be used to gain a cursory idea of when and what norms can evolve, the estimations obtained by running simulations can be costly to obtain, provide no guarantees about the behavior of the system, and may overlook some rare occurrences. We use a theoretical approach to analyze a system of agents playing a convergence game and develop models that predict (a) how the system's behavior will change over time, (b) how much time it will take for it to converge to a stable state, and (c) how often the system will converge to a particular norm.

ICML Conference 1999 Conference Paper

Learning User Evaluation Functions for Adaptive Scheduling Assistance

• Melinda T. Gervasio
• Wayne Iba
• Pat Langley

ICAPS Conference 1994 Conference Paper

Reactive and Automatic Behavior in Plan Execution

• Pat Langley
• Wayne Iba
• Jeff Shrager

Much of the work on execution assumes that the agent constantly senses the environment, which lets it respond immediately to errors or unexpected events. In this paper, we argue that this purely reactive strategy is only optimal if sensing is inexpensive, and we formulate a simple model of execution that incorporates the cost of sensing. We present an average-case analysis of this model, which shows that in domains with high sensing cost or low probability of error, a more automatic strategy, one with long intervals between sensing, can lead to less expensive execution. The analysis also shows that the distance to the goal has no effect on the optimal sensing interval. These results run counter to the prevailing wisdom in the planning community, but they promise a more balanced approach to the interleaving of execution and sensing.