Action Programming Languages by Michael Thielscher
Introduction.- Mathematical Preliminaries.- Procedural Action Programs.- Action Programs and Planning.- Declarative Action Programs.- Reactive Action Programs.- Suggested Further Reading.-
Graph Representation Learning
-
A Concise Introduction to Models and Methods for Automated Planning
-
Learning with Support Vector Machines
-
A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
-
Reasoning with Probabilistic and Deterministic Graphical Models
-
Human Computation
-
Learning and Decision-Making from Rank Data
-
Explainable Human-AI Interaction
-
Network Embedding
-
Predicting Human Decision-Making
-
Game Theory for Data Science
-
Strategic Voting
-
Statistical Relational Artificial Intelligence
-
A Short Introduction to Preferences
-
Case-Based Reasoning
-
Representing and Reasoning with Qualitative Preferences
-
Robot Learning from Human Teachers
-
Visual Object Recognition
-
General Game Playing
-
Essential Principles for Autonomous Robotics
-
Federated Learning
-
Graph-Based Semi-Supervised Learning
-
An Introduction to Constraint-Based Temporal Reasoning
-
Intelligent Autonomous Robotics
-
Answer Set Solving in Practice
-
Representation Discovery using Harmonic Analysis
-
Representations and Techniques for 3D Object Recognition and Scene Interpretation
-
Introduction to Intelligent Systems in Traffic and Transportation
-
Introduction to Symbolic Plan and Goal Recognition
-
Judgment Aggregation
-
Metric Learning
-
Data Integration
-
Trading Agents
-
Introduction to Semi-Supervised Learning
-
Transfer Learning for Multiagent Reinforcement Learning Systems
-
Introduction to Graph Neural Networks
-
Introduction to Logic Programming
-
An Introduction to the Planning Domain Definition Language
-
Lifelong Machine Learning, Second Edition
-
Adversarial Machine Learning
-
Multi-Objective Decision Making
-
Active Learning
-
Planning with Markov Decision Processes
-
Computational Aspects of Cooperative Game Theory
-
Algorithms for Reinforcement Learning
Michael Thielscher is a Professor and head of the Computational Logic Group at Dresden University in Germany since 1997. He received his PhD in Computer Science from Darmstadt University of Technology, Germany. His research is mainly in Knowledge Representation, Cognitive Robotics, Commonsense Reasoning, Game Playing, and Constraint Logic Programming. He has developed the action programming language and system FLUX and has published numerous papers and two books on knowledge representation for actions, on comparisons of different action languages, and on implementations of action programming systems. In 1998, his Habilitation thesis was honored with the award for research excellence by the alumni of Darmstadt University of Technology. He co-authored the program FLUXPLAYER, which in 2006 was crowned the world champion at the Second General Game Playing Competition in Boston.
| SKU | Unavailable |
| ISBN 13 | 9783031004193 |
| ISBN 10 | 3031004191 |
| Title | Action Programming Languages |
| Author | Michael Thielscher |
| Series | Synthesis Lectures On Artificial Intelligence And Machine Learning |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2008-07-08 |
| Number of pages | 91 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |