Search Results - (((((((kant OR agent) OR wantsa) OR makant) OR cantor) OR anne) OR slave) OR hints) algorithms.

In the tradition of Ahlfors and Bers : proceedings of the First Ahlfors-Bers Colloquium, Ahlfors-Bers Colloquium, November 6-8, 1998, State University of New York at Stony Brook

Table of Contents: “…Coverings of Cantor sets /…”
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Theory of computational complexity by Du, Dingzhu, Ko, Ker-I

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Fuzzy systems and data mining III : proceedings of FSDM 2017

Table of Contents: “…Fuzzy Control and Algorithms --…”
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Emerging military technologies : ethical and legal perspectives

Table of Contents: “…Discussing issues of responsibility, accountability and liability when AI agents decide and act during war the case of training algorithms for attacking possible targets /…”
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Artificial neural networks in biological and environmental analysis by Hanrahan, Grady

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Women in Numbers 2 : research directions in number theory : BIRS Workshop, WIN2 - Women in Numbers 2, November 6-11, 2011, Banff International Research Station, Banff, Alberta, Can... by David, Chantal, 1964-, Lalín, Matilde, 1977-, Manes, Michelle, 1970-

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Multimodal transport systems

Table of Contents: “…Multi-agent concept for a distributed car-pooling system --…”
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Key concepts & techniques in GIS by Albrecht, Jochen

Table of Contents: “…Agent-based modeling systems --…”
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Collective action 2.0 : the impact of social media on collective action by Spier, Shaked

Table of Contents: “…From an Individual Agent to an Active Collective --…”
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RF Positioning : Fundamentals, Applications, and Tools. by Campos, Rafael Saraiva

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The Princeton companion to mathematics

Table of Contents: “…Algorithms ;…”
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Optimization theory and related topics : Israel mathematical conference proceedings : a workshop in memory of Dan Butnariu, January 11-14, 2010, Haifa, Israel

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Rationality and decision making : from normative rules to heuristics

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When life is linear : from computer graphics to bracketology by Chartier, Timothy P.

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Advanced materials researches and application : selected, peer reviewed papers from the 2nd International Conference on Advanced Materials and its Application (AMA 2013), June 22-2...

Table of Contents: “…Effect of Anti-Cracking Agent on Cracking Property of SiO2 Optical Fiber Preform by Sol- Gel Method /…”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Introduction to Reinforcement Learning; What is RL?; RL algorithm; How RL differs from other ML paradigms; Elements of RL; Agent; Policy function; Value function; Model; Agent environment interface; Types of RL environment; Deterministic environment; Stochastic environment; Fully observable environment; Partially observable environment; Discrete environment; Continuous environment; Episodic and non-episodic environment; Single and multi-agent environment; RL platforms.…”
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New autonomous systems by Cardon, Alain, 1946-, Itmi, Mhamed

Table of Contents: “…Autonomous systems -- 1.3. Agents and multi-agent systems -- 1.4. Systems and organisms -- 1.5. …”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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