Sciweavers

Share
AI
2010
Springer

Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition

8 years 15 hour ago
Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition
How do we build algorithms for agent interactions with human adversaries? Stackelberg games are natural models for many important applications that involve human interaction, such as oligopolistic markets and security domains. In Stackelberg games, one player, the leader, commits to a strategy and the follower makes her decision with knowledge of the leader's commitment. Existing algorithms for Stackelberg games efficiently find optimal solutions (leader strategy), but they critically assume that the follower plays optimally. Unfortunately, in many applications, agents face human followers (adversaries) who -- because of their bounded rationality and limited observation of the leader strategy -- may deviate from their expected optimal response. In other words, human adversaries' decisions are biased due to their bounded rationality and limited observations. Not taking into account these likely deviations when dealing with human adversaries may cause an unacceptable degradati...
James Pita, Manish Jain, Milind Tambe, Fernando Or
Added 20 Mar 2011
Updated 20 Mar 2011
Type Journal
Year 2010
Where AI
Authors James Pita, Manish Jain, Milind Tambe, Fernando Ordóñez, Sarit Kraus
Comments (0)
books