The development of autonomous agents, such as mobile robots and software agents, has generated considerable research in recent years. Robotic systems, which are usually built from a mixture of continuous (analog) and discrete (digital) components, are often referred to as hybrid dynamical systems. Traditional approaches to real-time hybrid systems usually define behaviors purely in terms of determinism or sometimes non-determinism. However, this is insufficient as real-time dynamical systems very often exhibit uncertain behaviour. To address this issue, we develop a semantic model, Probabilistic Constraint Nets (PCN), for probabilistic hybrid systems
This work studies the combination of safe and probabilistic reasoning through the hybridization of M...
A wide variety of approaches exist for dealing with uncertainty in robotic reasoning, but relatively...
Constraint Nets have been developed as an algebraic on-line computational model of robotic systems. ...
The development of autonomous agents, such as mobile robots or software agents has generated consid...
AbstractHybrid dynamic systems are systems consisting of a nontrivial mixture of discrete and contin...
Robots are generally composed of electromechanical parts with multiple sensors and actuators. The ov...
AbstractIn this article, we recall different approaches to the constraint-based, symbolic analysis o...
An important issue in artificial intelligence and many other fields is modeling the domain of intere...
Abstract This paper proposes an approach for reducing the computational com-plexity of a model-predi...
This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predi...
The framework of hybrid discrete-continuous systems becomes increasingly popular for modeling and ve...
Recently, there has been a lot of attention for statistical relational learning and probabilistic pr...
Recently, there has been a lot of attention for statistical relational learning and probabilistic pr...
Hybrid continuous-time and discrete-event system models are developed for applications to intelligen...
金沢大学理工研究域電子情報学系We can model embedded systems as hybrid systems. Moreover, they are distributed and r...
This work studies the combination of safe and probabilistic reasoning through the hybridization of M...
A wide variety of approaches exist for dealing with uncertainty in robotic reasoning, but relatively...
Constraint Nets have been developed as an algebraic on-line computational model of robotic systems. ...
The development of autonomous agents, such as mobile robots or software agents has generated consid...
AbstractHybrid dynamic systems are systems consisting of a nontrivial mixture of discrete and contin...
Robots are generally composed of electromechanical parts with multiple sensors and actuators. The ov...
AbstractIn this article, we recall different approaches to the constraint-based, symbolic analysis o...
An important issue in artificial intelligence and many other fields is modeling the domain of intere...
Abstract This paper proposes an approach for reducing the computational com-plexity of a model-predi...
This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predi...
The framework of hybrid discrete-continuous systems becomes increasingly popular for modeling and ve...
Recently, there has been a lot of attention for statistical relational learning and probabilistic pr...
Recently, there has been a lot of attention for statistical relational learning and probabilistic pr...
Hybrid continuous-time and discrete-event system models are developed for applications to intelligen...
金沢大学理工研究域電子情報学系We can model embedded systems as hybrid systems. Moreover, they are distributed and r...
This work studies the combination of safe and probabilistic reasoning through the hybridization of M...
A wide variety of approaches exist for dealing with uncertainty in robotic reasoning, but relatively...
Constraint Nets have been developed as an algebraic on-line computational model of robotic systems. ...