Artificial Intelligence Today

Artificial Intelligence is one of the most fascinating and unusual areas of academic study to have emerged this century. For some, AI is a true scientific discipline, that has made important and fundamental contributions to the use of computation for our understanding of nature and phenomena of the human mind; for others, AI is the black art of computer science.
Artificial Intelligence Today provides a showcase for the field of AI as it stands today. The editors invited contributions both from traditional subfields of AI, such as theorem proving, as well as from subfields that have emerged more recently, such as agents, AI and the Internet, or synthetic actors. The papers themselves are a mixture of more specialized research papers and authorative survey papers.
The secondary purpose of this book is to celebrate Springer-Verlag's Lecture Notes in Artificial Intelligence series.

Inhalt

Behavioural Virtual Agents.- Logic-Based Knowledge Representation.- A Taxonomy of Theorem-Proving Strategies.- An Overview of Planning Under Uncertainty.- Knowledge Representation for Stochastic Decision Processes.- A Survey of Automated Deduction.- The World Wide Web as a Place for Agents.- Lifelike Pedagogical Agents and Affective Computing: An Exploratory Synthesis.- OBDD-based Universal Planning: Specifying and Solving Planning Problems for Synchronized Agents in Non-deterministic Domains.- Combining Artificial Intelligence and Databases for Data Integration.- "Underwater Love" Building Tristão and Isolda's Personalities.- An Oz-Centric Review of Interactive Drama and Believable Agents.- Robots with the Best of Intentions.- Agent-Based Project Management.- A System for Defeasible Argumentation, with Defeasible Priorities.- Handling Uncertainty in Control of Autonomous Robots.- The Event Calculus Explained.- Towards a Logic Programming Infrastructure for Internet Programming.- Towards Autonomous, Perceptive, and Intelligent Virtual Actors.- Temporally Invariant Junction Tree for Inference in Dynamic Bayesian Network.