Abstract not found

Based on the research done in the last decade, attempts have been made to propose description logics as unifying formalisms for the various class-based representation languages used in different areas. These attempts have made apparent that sound, complete, and decidable description logics still suffer from several limitations, regarding modeling classes of aggregate objects, expressing general inclusion axioms, and the ability of navigating links between classes. In this paper we make description logics accomplish the necessary leap in order to become suitable for the new challenging applications they are faced with. In particular, we propose a powerful description logic overcoming the above limitations and we show that its reasoning tasks are decidable in worst case exponential time. 1

Abstract not found

The paper describes an approach to reasoning about actions and plan generation within the framework of description logics. From an epistemological viewpoint, our approach is based on the formalization of actions given by dynamic logics, but we exploit their correspondence with description logics to turn the formalization into an actual implementation. In particular, we are able to carefully weaken the logical inference process, thus making the reasoning of the robot computationally feasible. From a practical viewpoint, we use a general purpose knowledge representation environment based on description logics, and its associated reasoning tools, in order to plan the actions of the mobile robot "Tino", starting from the knowledge about the environment and the action specification. The robot's reactive capabilities allow it to execute such plans in the real world.

this paper, we present a logic based framework for the representation of actions. Actions can change the meaning of properties of existing constants and their relationships. For instance "take" changes the properties of "on" and "hold": if somebody takes an object lying on a table then he/she will be holding this object after performing the action and the object will no longer be on the table. If somebody builds a wall, then the properties of bricks and cement will change. In logic oriented approaches, actions are frequently described by their preconditions and their results. The preconditions are represented by a formula which has to be true before the execution of the action and the results are represented by a formula which will be true after the action has been performed. In addition, the general laws of the world are described by formulas which have always to be true. An action occurs in a state of the world, which is also described by a formula, and yields a new state of the world which is obtained from the old state. Logic based action theories encounter typically the following problems:

Description Logics (DLs) are formalisms for taxonomic reasoning about structured knowledge. Adding the transitive closure of roles to DLs also enables them to represent and reason about actions and plans. The present paper explores several essentially different encodings of planning in Description Logics. We argue that DLs represent an ideal framework for analysing and comparing these approaches. Thus, we have identified two essentially different deductive encodings (a "causal" and a "symmetric" one), as well as a satisfiability-based approach. While the causal encoding is more appropriate for reasoning about precondition-triggered causal events, the symmetric encoding is more amenable to reasoning about possible outcomes of courses of actions without actually executing them (while allowing both progression and regression). In the deductive approaches, the existence of a plan corresponds to an inconsistency proof rather than to a model of some formula. Viewing planning as satisfiabili...

The paper describes an approach to reasoning about actions and plan generation within the framework of description logics. Our proposal is considered "classic" since it is in the style of deductive planning and it relies upon the reasoning capabilities of description logics, that are realized in the system Classic. From an epistemological point of view our approach is based on the formalization of actions given by dynamic logics, but we exploit their correspondence with description logics to turn the formalization into an actual implementation. In particular, we are able to carefully weaken the logical inference process, thus making the reasoning of the robot computationally feasible. From a practical viewpoint we use a general purpose knowledge-based environment based on description logics, and its associated reasoning tools, in order to plan the actions of the mobile robot "Tino", starting from the knowledge about the environment and the action specification. The robot's reactive cap...

The paper describes an approach to reasoning about actions and planning that starting from a logical formalization arrives at the realization of an actual agent, the mobile robot "Tino". The reasoning tools allow the robot to derive plans from the knowledge about the environment and the action specification, while its reactive capabilities allow it to execute its plans in the real world. The formalization is based on the propositional dynamic logics framework, but exploits the correspondence that exists between propositional dynamic logics and description logics, to carefully weaken the logical inference process in order to keep the reasoning tools of the robot both effective and efficient. Such reasoning tools are then implemented by making use of a general knowledge representation system based on description logics, namely the system CLASSIC. Introduction In Artificial Intelligence there has always been a great interest in the design of agents that can exhibit different forms of int...

Description Logics (DLs) are formalisms for taxonomic reasoning about structured knowledge. Adding the transitive closure of roles to DLs also enables them to represent and reason about actions and plans. The present paper explores several essentially different encodings of planning in Description Logics. We argue that DLs represent an ideal framework for analysing and comparing these approaches. Thus, we have identified two essentially different deductive encodings (a "causal" and a "symmetric" one), as well as a satisfiability-based approach. While the causal encoding is more appropriate for reasoning about precondition-triggered causal events, the symmetric encoding is more amenable to reasoning about possible outcomes of courses of actions without actually executing them (while allowing both progression and regression). In the deductive approaches, the existence of a plan corresponds to an inconsistency proof rather than to a model of some formula. Viewing planning as satisfiabilit...