title: Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.
abstract: Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent's actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches.
authors.affiliation: Departamento de Matem&#225;ticas, Estad&#237;stica y Computaci&#243;n, Universidad de Cantabria, Santander 39005, Spain. cristina.tirnauca@unican.es.
authors.forename: Cristina
authors.initials: C
authors.lastname: Tîrnăucă
authors.affiliation: Departamento de Matem&#225;ticas, Estad&#237;stica y Computaci&#243;n, Universidad de Cantabria, Santander 39005, Spain. joseluis.montana@unican.es.
authors.forename: José L
authors.initials: JL
authors.lastname: Montaña
authors.affiliation: Department of Computer Science, Drexel University, Philadelphia, PA 19104, USA. santi@cs.drexel.edu.
authors.forename: Santiago
authors.initials: S
authors.lastname: Ontañón
authors.affiliation: Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA. gonzalez@ucf.edu.
authors.forename: Avelino J
authors.initials: AJ
authors.lastname: González
authors.affiliation: Departamento de Matem&#225;ticas, Estad&#237;stica y Computaci&#243;n, Universidad de Cantabria, Santander 39005, Spain. luis.m.pardo@gmail.com.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Pardo
keywords: ambient intelligence; behavioral cloning; behavioral recognition; learning from observation; probabilistic finite automaton; virtual agents