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PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 10 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
150
Voted
SYNTHESE
2008
99views more  SYNTHESE 2008»
15 years 3 months ago
Public and private communication are different: results on relative expressivity
Dynamic Epistemic Logic (DEL) is the study of how to reason about knowledge, belief, and communication. This paper studies the relative expressivity of certain fragments of the DE...
Bryan Renne
131
Voted
WSC
2007
15 years 5 months ago
Using empirical demand data and common random numbers in an agent-based simulation of a distribution network
Agent-based simulation provides a methodology to investigate complex systems behavior, such as supply chains, while incorporating many empirical elements relative to both systems ...
William J. Sawaya
168
Voted
ILP
2007
Springer
15 years 9 months ago
Learning to Assign Degrees of Belief in Relational Domains
A recurrent question in the design of intelligent agents is how to assign degrees of beliefs, or subjective probabilities, to various events in a relational environment. In the sta...
Frédéric Koriche
127
Voted
ATAL
2004
Springer
15 years 8 months ago
A UML Based Approach for Modeling and Implementing Multi-Agent Systems
In this paper we present an agent-oriented modeling language, called MAS-ML, and an approach for mapping its diagrams into Java implementations. MAS-ML extends the UML meta-model ...
Viviane Torres da Silva, Ricardo Choren, Carlos Jo...