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Self-organizing multi-agent systems (MAS) use different mechanisms to mimic the adaptation exhibited by complex systems situated in unpredictable and dynamic environments. These mechanisms allow a collection of agents to spontaneously adapt their ...

This paper describes a proposal to build an intelligent feedback selection system for Virtual Reality-based training simulators. The system is aimed at generating multimodal feedback in real-time for advising the students while training with the ...

Physical agents (such as wheeled vehicles, UAVs, hovercraft, etc.) with simple control systems are often sensitive to changes in their physical design and control parameters. As such, it is crucial to evaluate the agent's control systems together with ...

A network of cooperating agents must be able to reach rough consensus on a set of topics for cooperation. With highly heterogeneous agents, however, incommensurable measures and imprecise translation render ordinary consensus algorithms inappropriate. I ...

When autonomous agents decide on their bidding strategies in real world auctions, they have a number of concerns that go beyond the models that are normally analyzed in traditional auction theory. Oftentimes, the agents have budget constraints and the ...

We are interested in verifying game-theoretic properties such as strategyproofness for auction protocols in open agent systems. Model checking provides an automatic way of carrying out such proofs. However it may suffer from state space explosion for ...

We develop strategy/false-name-proof multi-unit auction protocols that can handle non-quasi-linear utilities.

One almost universal assumption in auction theory literature is that each bidder has quasi-linear utility, except for some works on budget-...

Distributed allocation and multiagent coordination problems can be solved through combinatorial auctions (CAs). However, most of the existing winner determination algorithms (WDAs) for CAs are centralized. The PAUSE auction is one of a few efforts to ...

Mechanism design (MD) has recently become a very popular approach in the design of distributed systems of autonomous agents. A key assumption required for the application of MD is that agents behave rationally in the mechanism or game, since this ...

Auction methods have been successfully used for coordinating teams of robots in the multi-robot routing problem, a representative domain for multi-agent coordination. Solutions to this problem typically use bids computed using the shortest distance ...

We study collaboration among selfish agents in the tactical airport planning domain. This can be seen as a social exchange scenario, in which the efforts of performing tasks are the resources that are being exchanged. We investigate conditions under ...

We investigate equilibrium strategies for bidding agents that participate in multiple, simultaneous second-price auctions with perfect substitutes. For this setting, previous research has shown that it is a best response for a bidder to participate in ...

Multi-issue negotiation protocols represent a promising field since most negotiation problems in the real world involve multiple issues. Our work focuses on negotiation with interdependent issues, in which agent utility functions are nonlinear. Existing ...

We study the concept of bribery in the situation where voters are willing to change their votes as we ask them, but where their prices depend on the nature of the change we request. Our model is an extension of the one of Faliszewski et al. [9], where ...

We consider Effort Games, a game theoretic model of cooperation in open environments, which is a variant of the principal--agent problem from economic theory. In our multiagent domain, a common project depends on various tasks; achieving certain subsets ...

This paper presents the design and implementation of negotiation agents that negotiate with other entities for acquiring multiple resources. In our approach, agents utilize a time-dependent negotiation strategy in which the reserve price of each ...

In order to prevent misunderstandings within groups of interacting agents, it is necessary to ensure that the agents' beliefs regarding the overall state of the interaction are consistent with each other at all times. In [7], Paurobally et al. proposed ...

The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new framework that supports efficient approximate MAS-based sensor interpretation, ...

This paper addresses the issue of emergence of robust cooperation among self-interested agents interacting in N-player social dilemma games. A series of graphs are created each exhibiting a different level of community structure; we show the influence ...

This paper extends existing methods for information searching and sharing in large-scale, dynamic networks of agents, to deal with networks of heterogeneous agents: Agents that do not share a common conceptualization of information categories and agents ...