Milind Tambe

Publications
Influence

Adopt: asynchronous distributed constraint optimization with quality guarantees

Pragnesh Jay Modi, W. Shen, Milind Tambe, M. Yokoo
Mathematics, Computer Science
Artif. Intell.
2005

We propose a polynomial-space algorithm for DCOP named Adopt that is guaranteed to find the globally optimal solution while allowing agents to execute asynchronously and in parallel. Expand

Towards Flexible Teamwork

Milind Tambe
Computer Science
J. Artif. Intell. Res.
1 July 1997

We present a general, implemented model of teamwork, called STEAM, which enables agents to autonomously reason about coordination and communication, providing requisite flexibility and reusability. Expand

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The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models

David V. Pynadath, Milind Tambe
Computer Science
J. Artif. Intell. Res.
22 June 2011

We present a unified framework, the COMmunicative Multiagent Team Decision Problem (COM-MTDP), which combines and extends existing multiagent theories, such as decentralized partially observable Markov decision processes and economic team theory, to analyze the optimality and computational complexity of the teamwork problem. Expand

Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games

Praveen Paruchuri, J. Pearce, J. Marecki, Milind Tambe, F. Ordóñez, S. Kraus
Computer Science
AAMAS
12 May 2008

In a class of games known as Stackelberg games, one agent (the leader) must commit to a strategy that can be observed by the other agent ( the follower or adversary) before the adversary chooses its own strategy. Expand

Taming Decentralized POMDPs: Towards Efficient Policy Computation for Multiagent Settings

Ranjit Nair, Milind Tambe, M. Yokoo, David V. Pynadath, S. Marsella
Computer Science
IJCAI
9 August 2003

The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision process . Expand

Taking DCOP to the real world: efficient complete solutions for distributed multi-event scheduling

R. Maheswaran, Milind Tambe, E. Bowring, J. Pearce, Pradeep Varakantham
Computer Science
Proceedings of the Third International Joint…
19 July 2004

Distributed Constraint Optimization (DCOP) is an elegant formalism relevant to many areas in multiagent systems, yet complete algorithms have not been pursued for real world applications due to perceived complexity. Expand

Distributed Algorithms for DCOP: A Graphical-Game-Based Approach

R. Maheswaran, J. Pearce, Milind Tambe
Computer Science
ISCA PDCS
2004

This paper addresses the application of distributed constraint optimization problems to large-scale dynamic environments. Expand

Networked Distributed POMDPs: A Synergy of Distributed Constraint Optimization and POMDPs

Ranjit Nair, Pradeep Varakantham, Milind Tambe, M. Yokoo
Computer Science
IJCAI
9 July 2005

In many real-world multiagent applications such as distributed sensor nets, a network of agents is formed based on each agent's limited interactions with a small number of neighbors. Expand

Security and Game Theory - Algorithms, Deployed Systems, Lessons Learned

Milind Tambe
Engineering, Computer Science
12 December 2011

This is the first and only study of long-term deployed applications of game theory for security for Los Angeles International Airport police and the U.S. Federal Air Marshals Service. Expand

Allocating tasks in extreme teams

P. Scerri, A. Farinelli, S. Okamoto, Milind Tambe
Computer Science
AAMAS '05
25 July 2005

We propose a novel distributed task allocation algorithm for extreme teams, called LA-DCOP, that incorporates three key ideas. Expand

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