When robots weep : a computational approach to affective learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 245-262).This thesis presents a unified computational framework for the study of emotion that integrates several concepts and mechanisms which have been traditionally deemed to be integral components of intelligent behavior. We introduce the notion of affect programs as the primary theoretical constructs for investigating the function and the mechanisms of emotion, and instantiate these in a variety of embodied agents, including physical and simulated robots. Each of these affect programs establishes a functionally distinct mode of operation for the robots, that is activated when specific environmental contingencies are appraised. These modes involve the coordinated adjustment and entrainment of several different systems-including those governing perception, attention, motivation regulation, action selection, learning, and motor control-as part of the implementation of specialized solutions that take advantage of the regularities found in highly recurrent and prototypical environmental contingencies. We demonstrate this framework through multiple experimental scenarios that explore important features of the affect program abstraction and its function, including the demonstration of affective behavior, evaluative conditioning, incentive salience, and affective learning.by Juan David Velásquez.Ph.D

Ms. Pacrat: A feeling, thinking machine

Since before the time of the first digital computers, the workings of the mind have been compared to that of a machine. With the onset of the discipline of Artificial Intelligence a truly organized attempt has been made to build intelligent machines that model the mind. Many interesting programs have been built, but the legitimacy of their success is a matter of great controversy. None of the AI programs developed so far have come close to the true power and intelligence of the brain. Expert systems, for example, are the most success ful commercial AI programs, and even they have shown to be brittle, and only able to deal with knowledge in very narrow domains. I suggest that those interested in modeling the mind should explore the emotions. I propose that intelligence and the emotions have a dependent and critical relationship. This relationship suggests that attempts to model human intelligence should consider how the emotions effect our thinking, reasoning, problem-solving, and learning and incorporate this information into computer models. This thesis will review what has been done in the field of AI to build intelligent machines and will examine the relationship between emotions and intelligence. A computer model of emotions will be presented: MS. PACRAT - A Feeling Thinking Machine

Toward Building A Social Robot With An Emotion-based Internal Control

In this thesis, we aim at modeling some aspects of the functional role of emotions on an autonomous embodied agent. We begin by describing our robotic prototype, Cherry--a robot with the task of being a tour guide and an office assistant for the Computer Science Department at the University of Central Florida. Cherry did not have a formal emotion representation of internal states, but did have the ability to express emotions through her multimodal interface. The thesis presents the results of a survey we performed via our social informatics approach where we found that: (1) the idea of having emotions in a robot was warmly accepted by Cherry\u27s users, and (2) the intended users were pleased with our initial interface design and functionalities. Guided by these results, we transferred our previous code to a human-height and more robust robot--Petra, the PeopleBot--where we began to build a formal emotion mechanism and representation for internal states to correspond to the external expressions of Cherry\u27s interface. We describe our overall three-layered architecture, and propose the design of the sensory motor level (the first layer of the three-layered architecture) inspired by the Multilevel Process Theory of Emotion on one hand, and hybrid robotic architecture on the other hand. The sensory-motor level receives and processes incoming stimuli with fuzzy logic and produces emotion-like states without any further willful planning or learning. We will discuss how Petra has been equipped with sonar and vision for obstacle avoidance as well as vision for face recognition, which are used when she roams around the hallway to engage in social interactions with humans. We hope that the sensory motor level in Petra could serve as a foundation for further works in modeling the three-layered architecture of the Emotion State Generator