We study the model of projective simulation (PS), a novel approach to arti cial intelligence based on stochastic processing of episodic memory which was recently introduced [1]. Here we provide a detailed analysis of the model and examine its performance, including its achievable e ciency, its learning times and the way both properties scale with the problems' dimension. In addition, we situate the PS agent in di erent learning scenarios, and study its learning abilities. A variety of new scenarios are being considered, thereby demonstrating the model's exibility. Further more, to put the PS scheme in context, we compare its performance with those of Q-learning and learning classi er systems, two popular models in the eld of reinf...
Abstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamic...
The aim of this paper is to grasp the relevant distinctions between various ys in which models and s...
Team training in complex domains often requires a substantial number of resources, e.g. vehicles, ma...
This thesis explores the model of projective simulation (PS), a novel approach for an artificial int...
Projective simulation (PS) is a model for intelligent agents with a deliberation capacity that is ba...
The ability to generalize is an important feature of any intelligent agent. Not only because it may ...
Formation of stimulus equivalence classes has been recently modeled through equivalence projective s...
In this thesis, two well studied subjects in behavior analysis are computationally modeled; formatio...
Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human...
This research work presents a systematic investigational study of a challenging phenomenon observed ...
The contribution presents some first results concerning the usability of neural network, obtained fr...
Treball fi de màster de: Master in Cognitive Systems and Interactive MediaDirectors: Ismael T. Freir...
Given the recent advances within a subfield of machine learning called reinforcement learning, sever...
How to achieve efficient reinforcement learning in various training environments is a central challe...
This thesis explores structured, reward-based behaviour in artificial agents and in animals. In Part...
Abstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamic...
The aim of this paper is to grasp the relevant distinctions between various ys in which models and s...
Team training in complex domains often requires a substantial number of resources, e.g. vehicles, ma...
This thesis explores the model of projective simulation (PS), a novel approach for an artificial int...
Projective simulation (PS) is a model for intelligent agents with a deliberation capacity that is ba...
The ability to generalize is an important feature of any intelligent agent. Not only because it may ...
Formation of stimulus equivalence classes has been recently modeled through equivalence projective s...
In this thesis, two well studied subjects in behavior analysis are computationally modeled; formatio...
Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human...
This research work presents a systematic investigational study of a challenging phenomenon observed ...
The contribution presents some first results concerning the usability of neural network, obtained fr...
Treball fi de màster de: Master in Cognitive Systems and Interactive MediaDirectors: Ismael T. Freir...
Given the recent advances within a subfield of machine learning called reinforcement learning, sever...
How to achieve efficient reinforcement learning in various training environments is a central challe...
This thesis explores structured, reward-based behaviour in artificial agents and in animals. In Part...
Abstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamic...
The aim of this paper is to grasp the relevant distinctions between various ys in which models and s...
Team training in complex domains often requires a substantial number of resources, e.g. vehicles, ma...