Learning regular sets from queries and counterexamples
Information and Computation
The minimum consistent DFA problem cannot be approximated within and polynomial
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Crytographic limitations on learning Boolean formulae and finite automata
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Switching and Finite Automata Theory: Computer Science Series
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DIVERSITY-BASED INFERENCE OF FINITE AUTOMATA
DIVERSITY-BASED INFERENCE OF FINITE AUTOMATA
Infinite games: randomization, computability, and applications to online problems
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Efficient learning of typical finite automata from random walks
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Asking questions to minimize errors
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Learning fallible finite state automata
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Piecemeal learning of an unknown environment
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Diversity-based inference of finite automata
Journal of the ACM (JACM)
An optimal parallel algorithm for learning DFA
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
How many queries are needed to learn?
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Generalized teaching dimensions and the query complexity of learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
On learning bounded-width branching programs
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
How many queries are needed to learn?
Journal of the ACM (JACM)
Temporal sequence learning and data reduction for anomaly detection
ACM Transactions on Information and System Security (TISSEC)
Optimal constrained graph exploration
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Applying Learning by Examples for Digital Design Automation
Applied Intelligence
Bootstrap learning for place recognition
Eighteenth national conference on Artificial intelligence
Automated assumption generation for compositional verification
Formal Methods in System Design
Assume-Guarantee Verification for Interface Automata
FM '08 Proceedings of the 15th international symposium on Formal Methods
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Utility-based on-line exploration for repeated navigation in an embedded graph
Artificial Intelligence
Learning dynamics: system identification for perceptually challenged agents
Artificial Intelligence
Automated Behavioral Fingerprinting
RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
Automated assumption generation for compositional verification
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Learning from a smarter teacher
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Cost-sensitive reinforcement learning for adaptive classification and control
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Inference and analysis of formal models of botnet command and control protocols
Proceedings of the 17th ACM conference on Computer and communications security
Inferring finite automata with stochastic output functions and an application to map learning
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Process-based derivation of requirements for medical devices
Proceedings of the 1st ACM International Health Informatics Symposium
Securing netlist-level FPGA design through exploiting process variation and degradation
Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate Arrays
A theory of history dependent abstractions for learning interface automata
CONCUR'12 Proceedings of the 23rd international conference on Concurrency Theory
Guided GUI testing of android apps with minimal restart and approximate learning
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
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We present new algorithms for inferring an unknown finite-state automaton from its input/output behavior in the absence of a means of resetting the machine to a start state. A key technique used is inference of a homing sequence for the unknown automaton.Our inference procedures experiment with the unknown machine, and from time to time require a teacher to supply counterexamples to incorrect conjectures about the structure of the unknown automaton. In this setting, we describe a learning algorithm which, with probability 1-&dgr;, outputs a correct description of the unknown machine in time polynomial in the automaton's size, the length of the longest counterexample, and log (1/&dgr;). We present an analogous algorithm which makes use of a diversity-based representation of the finite-state system. Our algorithms are the first which are provably effective for these problems, in the absence of a “reset.”We also present probabilistic algorithms for permutation automata which do not require a teacher to supply counterexamples. For inferring a permutation automaton of diversity D, we improve the best previous time bound by roughly a factor of D3/logD.