Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Artificial Intelligence
Do the right thing: studies in limited rationality
Do the right thing: studies in limited rationality
A world championship caliber checkers program
Artificial Intelligence
Linear-space best-first search
Artificial Intelligence
The trailblazer search: a new method for searching and capturing moving targets
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Learning to act using real-time dynamic programming
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
ICS '95 Proceedings of the 9th international conference on Supercomputing
Real-time search for learning autonomous agents
Real-time search for learning autonomous agents
Exploring unknown environments with real-time search or reinforcement learning
Proceedings of the 1998 conference on Advances in neural information processing systems II
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
AI Magazine
Rumor routing algorthim for sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Moving-Target Search: A Real-Time Search for Changing Goals
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Admissible Heuristic Search Algorithm
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
Speeding up the Convergence of Real-Time Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Eighteenth national conference on Artificial intelligence
Controlling the learning process of real-time heuristic search
Artificial Intelligence
Performance bounds for planning in unknown terrain
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Differentiated surveillance for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
A Comparison of Fast Search Methods for Real-Time Situated Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Lookahead pathologies for single agent search
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Hierarchical A *: searching abstraction hierarchies efficiently
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Current Topics in Artificial Intelligence
Comparing real-time and incremental heuristic search for real-time situated agents
Autonomous Agents and Multi-Agent Systems
Performance simulations of moving target search algorithms
International Journal of Computer Games Technology - Artificial Intelligence for Computer Games
Novel moving target search algorithms for computer gaming
Computers in Entertainment (CIE) - SPECIAL ISSUE: Media Arts and Games (Part II)
Pessimistic Heuristics Beat Optimistic Ones in Real-Time Search
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Thinking Too Much: Pathology in Pathfinding
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Graph abstraction in real-time heuristic search
Journal of Artificial Intelligence Research
Adaptive stochastic resource control: a machine learning approach
Journal of Artificial Intelligence Research
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Real-time heuristic search with a priority queue
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Efficient incremental search for moving target search
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
On learning in agent-centered search
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A mean-based approach for real-time planning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Case-based subgoaling in real-time heuristic search for video game pathfinding
Journal of Artificial Intelligence Research
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Escaping heuristic depressions in real-time heuristic search
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Automatic state abstraction for pathfinding in real-time video games
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Real-time heuristic search with depression avoidance
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Avoiding and escaping depressions in real-time heuristic search
Journal of Artificial Intelligence Research
Weighted real-time heuristic search
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Expert Systems with Applications: An International Journal
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Real-time search methods are suited for tasks in which the agent is interacting with an initially unknown environment in real time. In such simultaneous planning and learning problems, the agent has to select its actions in a limited amount of time, while sensing only a local part of the environment centered at the agent's current location. Real-time heuristic search agents select actions using a limited lookahead search and evaluating the frontier states with a heuristic function. Over repeated experiences, they refine heuristic values of states to avoid infinite loops and to converge to better solutions. The wide spread of such settings in autonomous software and hardware agents has led to an explosion of real-time search algorithms over the last two decades. Not only is a potential user confronted with a hodgepodge of algorithms, but he also faces the choice of control parameters they use. In this paper we address both problems. The first contribution is an introduction of a simple three-parameter framework (named LRTS) which extracts the core ideas behind many existing algorithms. We then prove that LRTA*, Ε-LRTA* , SLA*, and γ-Trap algorithms are special cases of our framework. Thus, they are unified and extended with additional features. Second, we prove completeness and convergence of any algorithm covered by the LRTS framework. Third, we prove several upper-bounds relating the control parameters and solution quality. Finally, we analyze the influence of the three control parameters empirically in the realistic scalable domains of real-time navigation on initially unknown maps from a commercial role-playing game as well as routing in ad hoc sensor networks.