Starting from some simple observations on a popular selection method in Evolutionary Algorithms (EAs)—tournament selection—we highlight a previously-unknown source of inefficiency. This leads us to rethink the order in which operations are performed within EAs, and to suggest an algorithm—the EA with efficient macro-selection—that avoids the inefficiencies associated with tournament selection. ...

Datalog-based systems often materialise all consequences of a datalog program and the data, allowing users’ queries to be evaluated directly in the materialisation. This process, however, can be computationally intensive, so most systems update the materialisation incrementally when input data changes. We argue that existing solutions, such as the wellknown Delete/Rederive (DRed) algorithm, can...

Both materialization and backward-chaining as different modes of performing inference have complementary advantages and disadvantages. Materialization enables very efficient responses at query time, but at the cost of an expensive up front closure computation, which needs to be redone every time the knowledge base changes. Backward-chaining does not need such an expensive and change-sensitive p...

This paper treats the problem of implementing efficiently recursive Horn Clauses queries, including those with function symbols. In particular, the situation is studied where the initial bindings of the arguments in the recursive query goal can be used in the top-down (as in backward chaining) execution phase to improve the efficiency and, often, to guarantee the termination, of the forward cha...

Focusing is traditionally seen as a means of reducing inessential nondeterminism in backward-reasoning strategies such as uniform proof-search or tableaux systems. In this paper we construct a form of focused derivations for propositional linear logic that is appropriate for forward reasoning in the inverse method. We show that the focused inverse method conservatively generalizes the classical...

Capitalisation of search processes becomes a real challenge in many domains. By search process, we mean a sequence of queries that enables a community member to find comprehensive and accurate information by composing results from different information sources. In this paper we propose a intentional model based on semantic Web technologies and models and aiming both at the capitalization, reuse...

The Graphplan algorithm exemplifies the speed-up achieveable with disjunctive representations that leverage opposing directions of refinement. It is in this spirit that we introduce Bsrgraphplan, a work in progress intended to address issues of scalability and expressiveness which are problematic for Graphplan. Specifically, we want to endow the planner with intelligent backtracking and full qu...

The Expressive Intelligence Studio is developing a new approach to freeform conversational interaction in playable media that combines dialogue management, natural language generation (NLG), and natural language understanding. In this paper, we present our method for dialogue generation, which has been fully implemented in a game we are developing called Talk of the Town. Eschewing a traditiona...

Since the notion of general purpose planning became one of the touchstones of artificial intelligence, surprisingly little improvement has been made in the efficiency of planning algorithms. Efficient high-speed search is essential to most planning algorithms proposed to date: this can only be achieved if the search algorithms used are based on a solid understanding of the search space. The con...