On complexity as bounded rationality (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Robot navigation with range queries
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
SIAM Journal on Computing
How to Explore your Opponent's Strategy (almost) Optimally
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Application of automata learning algorithms to robot motion tracking
ISPRA'05 Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation
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The paper studies the problem of tracking a target robot that moves following a random walk strategy, by constructing in the observer robot a model of the behaviour of the target. The strategy of the target robot is supposed to be a random generator of movements. We make the assumption that the robot motion strategies can be modelled as uniform random generator of movements. We suppose that the observations are noise free. We will explore the hardness of the problem of trying to predict the numbers generated by a uniform random generator and relate this problem with our motion tracking problem. At the end of the present article we will propose some algorithmic alternatives to deal with the complexity of this problem.