Emergent communication has made strides towards learning communication from scratch, but has focused primarily on protocols that resemble human language. In nature, multi-agent cooperation gives rise to a wide range of communication that varies in ...

Computer and information scientists join forces with other fields to help solve societal and environmental challenges facing humanity, in pursuit of a sustainable future.

Markov Decision Processes are one of the most widely used frameworks to formulate probabilistic planning problems. Since planners are often risk-sensitive in high-stake situations, non-linear utility functions are often introduced to describe their ...

In [1], we introduced a novel distributed inference algorithm for the multiagent Gaussian inference problem, based on the framework of graphical models and message passing algorithms. We compare it to current state of the art techniques and we ...

The problem of multiagent Gaussian inference in a dynamic environment, also known as distributed Kalman filtering, is formulated into the framework of message passing algorithms. Upon generalizing the derivation of the standard Kalman filter to the ...

Decimation is a simple process for solving constraint satisfaction problems, by repeatedly fixing variable values and simplifying without reconsidering earlier decisions. We investigate different decimation strategies, contrasting those based on local, ...

In this paper we compute Bayes-Nash equilibria for first price single unit auctions and m^th price multi unit auctions, when the auction has a set of possible closing times, one of which is chosen randomly for the auction to end at. Thus the auctions ...

In previous work we have introduced a principled methodology for systematically exploring the space of bidding strategies when agents participate in a significant number of simultaneous auctions, and thus finding an analytical solution is not possible. ...

In previous work we have introduced a principled methodology for systematically exploring the space of bidding strategies when agents participate in a significant number of simultaneous auctions, and thus finding an analytical solution is not possible. ...

We are interested in finding natural communities in large-scale linked networks. Our ultimate goal is to track changes over time in such communities. For such temporal tracking, we require a clustering algorithm that is relatively stable under small ...

In this paper we present a methodology for deciding the bidding strategy of agents participating in a significant number of simultaneous auctions, when finding an analytical solution is not possible. We decompose the problem into sub-problems and then ...

We describe theoretical results and empirical study of context-sensitive restart policies for randomized search procedures. The methods generalize previous results on optimal restart policies by exploiting dynamically updated beliefs about the ...

Computational efficiency is a central concern in the design of knowledge representation systems. In order to obtain efficient systems, it has been suggested that one should limit the form of the statements in the knowledge base or use an incomplete ...