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AAAI
2008
14 years 18 days ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
AAAI
2000
13 years 11 months ago
Applying Learnable Evolution Model to Heat Exchanger Design
A new approach to evolutionary computation, called Learnable Evolution Model (LEM), has been applied to the problem of optimizing tube structures of heat exchangers. In contrast t...
Kenneth A. Kaufman, Ryszard S. Michalski
IAT
2008
IEEE
13 years 10 months ago
Planning with iFALCON: Towards A Neural-Network-Based BDI Agent Architecture
This paper presents iFALCON, a model of BDI (beliefdesire-intention) agents that is fully realized as a selforganizing neural network architecture. Based on multichannel network m...
Budhitama Subagdja, Ah-Hwee Tan
ATAL
2006
Springer
14 years 2 months ago
A stochastic language for modelling opponent agents
There are numerous cases where a reasoning agent needs to reason about the behavior of an opponent agent. In this paper, we propose a hybrid probabilistic logic language within wh...
Gerardo I. Simari, Amy Sliva, Dana S. Nau, V. S. S...
AAMAS
2002
Springer
13 years 10 months ago
The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents
Abstract. The purpose of this research is to show the relevance of philosophical theories to agent knowledge base (AKB) design, implementation, and behaviour. We will describe how ...
Nicholas Lacey, Mark Lee