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ICRA
2008
IEEE
136views Robotics» more  ICRA 2008»
14 years 4 months ago
Multi-agent probabilistic search in a sequential decision-theoretic framework
— Consider the task of searching a region for the presence or absence of a target using a team of multiple searchers. This paper formulates this search problem as a sequential pr...
Timothy H. Chung, Joel W. Burdick
JMLR
2012
12 years 10 days ago
Adaptive MCMC with Bayesian Optimization
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...
Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando d...
ICANN
1997
Springer
14 years 2 months ago
On Learning Soccer Strategies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
ML
1998
ACM
117views Machine Learning» more  ML 1998»
13 years 9 months ago
Learning Team Strategies: Soccer Case Studies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
BIBE
2007
IEEE
113views Bioinformatics» more  BIBE 2007»
14 years 4 months ago
Quantitative and Probabilistic Modeling in Pathway Logic
—This paper presents a study of possible extensions of Pathway Logic to represent and reason about semiquantitative and probabilistic aspects of biological processes. The underly...
Alessandro Abate, Yu Bai, Nathalie Sznajder, Carol...