Towards a general theory of action and time
Artificial Intelligence
Temporal reasoning based on semi-intervals
Artificial Intelligence
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Maintaining knowledge about temporal intervals
Communications of the ACM
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Scaling Reinforcement Learning toward RoboCup Soccer
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Recognizing Probabilistic Opponent Movement Models
RoboCup 2001: Robot Soccer World Cup V
Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer
RoboCup 2001: Robot Soccer World Cup V
RoboCup 2000: Robot Soccer World Cup IV
Recognizing Formations in Opponent Teams
RoboCup 2000: Robot Soccer World Cup IV
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Discovering tactical behavior patterns supported by topological structures in soccer agent domains
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Team Playing Behavior in Robot Soccer: A Case-Based Reasoning Approach
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Intuitive Plan Construction and Adaptive Plan Selection
RoboCup 2007: Robot Soccer World Cup XI
Incremental Generation of Abductive Explanations for Tactical Behavior
RoboCup 2007: Robot Soccer World Cup XI
A case-based approach for coordinated action selection in robot soccer
Artificial Intelligence
Discovering behavior patterns in multi-agent teams
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
Action prediction of opponents in MMORPG using data stream mining approach with heuristic motions
ISTASC'10 Proceedings of the 10th WSEAS international conference on Systems theory and scientific computation
Classifying agent behaviour through relational sequential patterns
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Analysing the behaviour of robot teams through relational sequential pattern mining
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Learning curve in concept drift while using active learning paradigm
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
Analysis of strategy in robot soccer game
Neurocomputing
Information Sciences: an International Journal
An overview on opponent modeling in RoboCup soccer simulation 2D
Robot Soccer World Cup XV
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Agents in dynamic environments have to deal with world representations that change over time. In order to allow agents to act autonomously and to make their decisions on a solid basis an interpretation of the current scene is necessary. If intentions of other agents or events that are likely to happen in the future can be recognized the agent's performance can be improved as it can adapt the behavior to the situation. In this work we present an approach which applies unsupervised symbolic learning off-line to a qualitative abstraction in order to create frequent patterns in dynamic scenes. These patterns can be later applied during runtime in order to predict future situations and behaviors. The pattern mining approach was applied to two games of the 2D RoboCup simulation league.