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NIPS
2007
15 years 5 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
AAAI
2000
15 years 5 months ago
Defining and Using Ideal Teammate and Opponent Agent Models
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
Peter Stone, Patrick Riley, Manuela M. Veloso
FTCS
1998
114views more  FTCS 1998»
15 years 5 months ago
Verification of a Safety-Critical Railway Interlocking System with Real-Time Constraints
Ensuring the correctness of computer systems used in lifecritical applications is very difficult. The most commonly used verification methods, simulation and testing, are not exha...
Vicky Hartonas-Garmhausen, Sérgio Vale Agui...
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AAAI
1997
15 years 5 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
DIALM
2010
ACM
146views Algorithms» more  DIALM 2010»
15 years 5 months ago
Regional consecutive leader election in mobile ad-hoc networks
In this paper we introduce the regional consecutive leader election (RCLE) problem, which extends the classic leader election problem to the ever-changing environment of mobile ad-...
Hyun Chul Chung, Peter Robinson, Jennifer L. Welch