Preemptive scheduling under time and resource constraints
IEEE Transactions on Computers - Special Issue on Real-Time Systems
Artificial Intelligence
Specification and Analysis of Real-Time Problem Solvers
IEEE Transactions on Software Engineering
Constraint-Based Searching: Algorithms and Architectures
Constraint-Based Searching: Algorithms and Architectures
Real-Time Search for Autonomous Agents and Multiagent Systems
Autonomous Agents and Multi-Agent Systems
Cognition, Sociability, and Constraints
Balancing Reactivity and Social Deliberation in Multi-Agent Systems, From RoboCup to Real-World Applications (selected papers from the ECAI 2000 Workshop and additional contributions)
A Dynamic Scheduling Benchmark: Design, Implementation and Performance Evaluation
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
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Real-time algorithms need to address the time constraints (e.g. deadlines) imposed by applications like process control and robot navigation. Furthermore, dependable real-time algorithms need to be predictable about their ability to meet the time constraints of given tasks. A real-time algorithm is predictable, if it can decide the feasibility of meeting time constraints of a given task or an arbitrary task from a task set well ahead of the deadline. Lastly, a real-time algorithm should exhibit progressively optimizing behavior (i.e. the quality of the solution produced should improve as time constraints are relaxed). We propose a new algorithm, SARTS, that is based on a novel on-line technique to choose the proper values of parameters which control the time allocated to planning based on the time constraints. SARTS also provides criteria to predict its ability to meet the time constraints of a given task. The paper provides theoretical and experimental characterization of SARTS as a dependable real-time algorithm.