The capabilities for representing and reasoning about three-dimensional (3-D) objects are essential for knowledge-based, 3-D photointerpretation systems that combine domain knowledge with image processing, as demonstrated by 3- D Mosaic and ACRONYM. Three-dimensional representation of objects is necessary for many additional applications, such as robot navigation and 3-D change detection. Geometric reasoning is especially important because geometric relationships between object parts are a rich source of domain knowledge. A practical framework for geometric representation and reasoning must incorporate projections between a two-dimensional (2-D) image and a 3-D scene, shape and surface properties of objects, and geometric and topological relationships between objects. In addition, it should allow easy modification and extension of the system's domain knowledge and be flexible enough to organize its reasoning efficiently to take advantage of the current available knowledge.

This book provides a tutorial introduction to modern techniques for representing and reasoning about qualitative preferences with respect to a set of alternatives. The syntax and semantics of several languages for representing preference languages, including CP-nets, TCP-nets, CI-nets, and CP-theories, are reviewed. Some key problems in reasoning about preferences are introduced, including determining whether one alternative is preferred to another, or whether they are equivalent, with respect to a given set of preferences. These tasks can be reduced to model checking in temporal logic. Specifically, an induced preference graph that represents a given set of preferences can be efficiently encoded using a Kripke Structure for Computational Tree Logic (CTL).

We introduce a novel qualitative preference representation language, preference trees , or P-trees . We show that the lan- guage is intuitive to specify preferences over combinatorial domains and it extends existing preference formalisms such as LP-trees , ASO-rules and possibilistic logic . We study rea- soning problems with P-trees and obtain computational com- plexity results.

The paper develops a branching-time ontology that maintains the classical restriction of forward movement through a temporal tree structure, but permits the representation of paths in which one can perform inferences about time-travel scenarios. Central to the ontology is the notion of an agent embodiment whose beliefs are equivalent to those of an agent who has time-traveled from the future.

There is a growing interest within educational research to produce culturally-aware intelligent learning environments (ILEs) that capitalize on the affective benefits of positive cultural resonance and avoid the counter-productive effects of culturally ignorant designs. Several challenges arise when attempting to produce culturally-appropriate content for ILEs. These stem from the need for semantic representations of cultural conceptualisations that go beyond folk approaches, have sufficient details for intracultural reasoning, and which can be matched with the cultural backgrounds of students who use these ILEs. This paper tackles these challenges firstly through the formalism of a lower-level ontology for describing the cultural semantics commonly used in educational content and secondly with a software component for reasoning about this ontological knowledge in relation to student cultural backgrounds. An application was developed to test the practicality of the approach and assess its utility in locating culturally-appropriate educational resources for students. The evaluation results revealed that the majority of content selections made by the system were rated as highly appropriate by 90% of the participants on average and confirmed the viability of the approach.

A general game player is a system that can play previously unknown games just by being given their rules. For this purpose, the Game Description Language (GDL) has been developed as a high-level knowledge representation formalism to communicate game rules to players. In this paper, we address a fundamental limitation of state-of-the-art methods and systems for General Game Playing, namely, their being confined to deterministic games with complete information about the game state. We develop a simple yet expressive extension of standard GDL that allows for formalising the rules of arbitrary finite, n-player games with randomness and incomplete state knowledge. In the second part of the paper, we address the intricate reasoning challenge for general game-playing systems that comes with the new description language. We develop a full embedding of extended GDL into the Situation Calculus augmented by Scherl and Levesque's knowledge fluent. We formally prove that this provides a sound and complete reasoning method for players' knowledge about game states as well as about the knowledge of the other players.

Many applications, e.g., Web service composition, complex system design, team formation, etc., rely on methods for identifying collections of objects or entities satisfying some functional requirement. Among the collections that satisfy the functional requirement, it is often necessary to identify one or more collections that are optimal with respect to user preferences over a set of attributes that describe the non-functional properties of the collection. We develop a formalism that lets users express the relative importance among attributes and qualitative preferences over the valuations of each attribute. We define a dominance relation that allows us to compare collections of objects in terms of preferences over attributes of the objects that make up the collection. We establish some key properties of the dominance relation. In particular, we show that the dominance relation is a strict partial order when the intra-attribute preference relations are strict partial orders and the relative importance preference relation is an interval order. We provide algorithms that use this dominance relation to identify the set of most preferred collections. We show that under certain conditions, the algorithms are guaranteed to return only (sound), all (complete), or at least one (weakly complete) of the most preferred collections. We present results of simulation experiments comparing the proposed algorithms with respect to (a) the quality of solutions (number of most preferred solutions) produced by the algorithms, and (b) their performance and efficiency. We also explore some interesting conjectures suggested by the results of our experiments that relate the properties of the user preferences, the dominance relation, and the algorithms.

We summarise the experimental design issues related to timing in several human-robot interaction scenarios investigating turn-taking or synchronization between child-sized humanoid robots and human participants. Our aim is not to have the humanoid robots just replicate the human’s behaviours (e.g. waving, peek-a-boo, or drumming), but to engage in interactions in a socially appropriate manner. From these various studies, we have identified several ways in which time has an impact on interaction. We have also identified practical concerns about data collection for time-dependent interactions and ways to address them. The conclusions drawn from this work is likely to be useful in informing the design of systems which engage in synchronized or turn-taking interactions with people.

The author makes an important scientific contribution to the theory of knowledge and automatic decision making. The book will be a reference on fundamental research as well as a useful instrument for scientists, philosophers, and advanced students. The book's structure is constructive, facilitating a clear transmission of the author's ideas. Bacchus uses two plans of exposition: the epistemological plan justifies his theory in a wide, philosophical perspective, and the formal, mathematical plan gives the reader a valuable instrument. The book may be too short to fulfill the author's goals, but it reports a research result and requires the reader to take a good look at the bibliography.