Traditional centralised approaches to security are difficult to apply to large, distributed marketplaces in which software agents operate. Developing a notion of trust that is ba...
We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from mu...
In this paper, we embed an incentive-compatible, efficient, and individual rational payment scheme into our cost- and stability-based routing protocol in ad hoc networks which co...
We analyze the asymptotic behavior of agents engaged in an infinite horizon partially observable stochastic game as formalized by the interactive POMDP framework. We show that whe...
We design an incentive-compatible mechanism for scheduling n non-malleable parallel jobs on a parallel system comprising m identical processors. Each job is owned by a selfish us...