Francisco Toledo

Topics in Artificial Intelligence

In this paper we present CAT-CBR a component-based platform for developing CBR systems. CAT-CBR uses UPML (Universal Problem-solving Methods Language) for specifying CBR components. A collection of CBR components for retrieval of propositional cases is presented in detail. The CAT-CBR platform guides the engineer using a case-based recommendations system to develop a configuration of components that satisfies the requirements of a CBR system application. We also present how to develop a runtime CBR application from the configuration resultant of the configuring process.

Autonomous robot navigation using human spatial concepts

With the aim of automatically reasoning with spatial aspects in a cognitive way, several qualitative models have been developed in recent years. However, there is no model to reason with several spatial aspects in a uniform way. Moreover, most of these models simplify spatial objects to points. In this paper we present the use of constraint logic programming instantiated to finite domains extended with constraint handling rules as a tool for successfully integrating the qualitative concepts of orientation, distance, and cardinal directions, using points as well as extended objects as a primitive of reasoning. The resulting model has been applied to build a demonstrator: a qualitative navigation simulator on the structured environment of our city. ©2000 John Wiley & Sons, Inc.

A Framework Based on CLP Extended with CHRs for Reasoning with Qualitative Orientation and Positional Information

Several qualitative models have been developed in the last years with the aim of simulating the spatial reasoning process used by humans. However, up to now no model has been developed to represent and reason with several aspects of space (such as orientation, distance and cardinal directions, for instance) in a uniform way, i.e. by referring to the same spatial objects. An approach for the integration of several aspects of space into the same model, based on constraint logic programming extended with constraint handling rules, is proposed in this article. As an example of this approach, the integration of orientation and positional information in the same model is explained.

Representing and Reasoning on Three-Dimensional Qualitative Orientation Point Objects

An approach for representing and reasoning with 3-D qualitative orientation of point objects is presented. The model in 3-D is an extension of the Zimmerman and Freksa orientation model in 2-D. The paper presents attempts to represent 3-D spatial orientation in a final 3-D model. An iconic notation for 3-D spatial orientation relations is presented and the algebra is also explained.

The Integration of Qualitative Orientation and Named Distances: Application to a Qualitative Navigation Simulator

Human beings reason about different aspects of space (such as relative orientation, cardinal directions, distance, size and shape of objects) quite easily. With the aim of simulating human behavior, several models for these spatial concepts have been developed in the recent years. Cognitive considerations have made these frameworks qualitative, because they seem to deal better with the imprecision that human perception provides. However, an operational model to reason with all these spatial aspects in an integrated way has not been developed, up to now. The first aim of our research work has been the integration of different spatial concepts into the same spatial model which has been accomplished thanks to the definition of an operational model based on Constrain Logic Programming extended with Constraint Handling Rules. Although other aspects of space have been successfully represented by these techniques [2], in this paper we focus our attention in positional information, that is, orientation integrated with distance information. The Constraint Solver developed for managing positional information has a temporal complexity of O(n)3, where n is the number of spatial landmarks considered in the reasoning process. The second aim of our work is to apply qualitative spatial reasoning to develop a Qualitative Navigation Simulator.

Integrating 3D Orientation Models

The 2-D orientation model of Freksa and Zimmerman has been extended by us into a 3-D orientation model for fine information. When the information provided to the system is coarse or it is advisable to reduce the processing time of the reasoning process, it is necessary to define a coarse 3-D orientation model. Our orientation model has been coarse into three models, (a length coarse model, a height coarse model and a general coarse model) which have been explained in this paper. The management of different levels of granularity and the integration between the coarse and the fine 3-D orientation models has also been explained.

An Agent for Providing the Optimum Cycle Length Value in Urban Traffic Areas Constrained by Soft Temporal Deadlines

This paper puts forward a method for calculating the optimum duration for every group of intersection controllers working on the same cycle. It uses a process of deep reasoning to deal with problems related to uncertainty and unavailability of sensor data. Furthermore, this process is constrained by soft temporal deadlines. Its execution can be disturbed by interactions of other agents or by external control actions performed by the human operator. The method is implemented as the primary task of an agent which collaborates with other agents to deal with various open problems concerning urban traffic. This paper shows that its execution, in isolation or together with other agents, is stable and provides suitable results.

Cardinal Directions on Extended Objects for Qualitative Navigation

With the aim of simulating the human reasoning process about spatial aspects such as orientation, distance and cardinal directions, several qualitative models have been developed in the last years. However, there is no model for representing and reasoning with all these spatial aspects in a uniform way. In the approach presented in this paper, this integration has been accomplished thanks to consider each type of spatial relationship an instance of the Constraint Satisfaction Problem. Constraint Logic Programming instantiated to Finite Domains extended with Constraint Handling Rules is a programming paradigm which provides the suited level of abstraction to define an incremental, flexible, efficient -with polynomial cost- and general purpose Constraint Solver (CS) for each one of the spatial aspects to be integrated. Moreover, it also allows the use of point and extended objects as primitive of reasoning. The corresponding CS for cardinal directions is described in this paper. This model has been applied to the development of a Qualitative Navigator Simulator.

A Centralised Hierarchical Task Scheduler for an Urban Traffic Control System Based on a Multiagent Architecture

In this paper we present a scheduler suitable to be applied to a particular class of dynamic systems, which main characteristics are the lack of actual data during long time periods and the unreliability on the available data. The management of these systems requires the integration of simulation techniques, temporal reasoning, soft real-time and mechanisms of reason maintenance. To deal with all of these qualities it is showed a centralized hierarchical task scheduler, which main operation characteristics are event oriented and hierarchical task oriented. We apply this scheduler to a deep knowledge expert system developed for monitoring and helping to the decision taking in an urban traffic control system.