Emotional Memory and Adaptive Personalities

Emotional Memory and Adaptive Personalities

Anthony G. Francis Jr. (Google, USA), Manish Mehta (Georgia Institute of Technology, USA) and Ashwin Ram (Georgia Institute of Technology, USA)
DOI: 10.4018/978-1-60566-354-8.ch020
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Believable agents designed for long-term interaction with human users need to adapt to them in a way which appears emotionally plausible while maintaining a consistent personality. For short-term interactions in restricted environments, scripting and state machine techniques can create agents with emotion and personality, but these methods are labor intensive, hard to extend, and brittle in new environments. Fortunately, research in memory, emotion and personality in humans and animals points to a solution to this problem. Emotions focus an animal’s attention on things it needs to care about, and strong emotions trigger enhanced formation of memory, enabling the animal to adapt its emotional response to the objects and situations in its environment. In humans this process becomes reflective: emotional stress or frustration can trigger re-evaluating past behavior with respect to personal standards, which in turn can lead to setting new strategies or goals. To aid the authoring of adaptive agents, we present an artificial intelligence model inspired by these psychological results in which an emotion model triggers case-based emotional preference learning and behavioral adaptation guided by personality models. Our tests of this model on robot pets and embodied characters show that emotional adaptation can extend the range and increase the behavioral sophistication of an agent without the need for authoring additional hand-crafted behaviors.
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When we see a pet we’ve met before, we recall not just its name and temperament but how our interactions with it made us feel. We feel happy when we see the dog we had fun playing with, and feel sour about the cat that shocked us with its hiss. And just as we learn from them, they learn from us; the dog, remembering its happiness upon playing with us, may seek us out when we are down; and the cat, remembering our shocked reaction when it hissed, may avoid us, or be more cautious with its anger in the future. Pets don’t need to be ‘configured’ to live with us, and neither do we: all we need is the ability to react emotionally to our situations, a memory for our past emotional states, and the ability to let those recalled emotions color our current emotional state and guide our behaviors appropriately. We argue that robots and synthetic characters should have the same ability to interpret their interactions with us, to remember these interactions, and to recall them appropriately as a guide for future behaviors, and we present a working model of how this can be achieved.

Of course, humans are more complicated than pets; we have not just emotions but also ideals for our behavior, and can modify our reactions and plans when they violate our ideals. We may snarl back at the hissing cat, but that outburst of emotion can make us reconsider when we should show anger. Even if we do not reconsider at first, if we see the same cat multiple times we may eventually be prompted to figure out why it continues to try to enter our new home, to realize it was probably abandoned, and to change our routines to leave food for it – turning a hissing cat into a new companion. It may seem a tall order make robots have this kind of flexibility – but we argue it is possible by using emotion to trigger behavior revision guided by a personality model, and we present a working model of how it can be achieved.

In this chapter, we review efforts to build agents with believable personalities, point out problems particular to making these personalities convincing over long-term interactions with human users, and discuss research in cognitive science into the mechanisms of memory, emotion, and personality. Based on these psychological results, we present a method for building believable agents that uses emotion and memory to adapt an agent’s personality over time. We then present two case studies illustrating this idea, the first demonstrating emotional long term memory in a robot, and the second demonstrating emotion-driven behavioral updates in an embodied character. Finally, we conclude with lessons learned.

Key Terms in this Chapter

Blame Assignment: In learning and adaptation, blame assignment is the process of identifying the causes of a failure of a computational system to deliver the behaviors desired of it.

ABL (A Behavior Language): ABL is a programming language explicitly designed to support programming idioms for the creation of reactive, believable agents (Mateas and Stern, 2004). ABL has been successfully used to author the central characters Trip and Grace for the interactive drama Facade (Mateas and Stern, 2003). The ABL compiler is written in Java and targets Java; the generated Java code is supported by the ABL runtime system.

Appraisal: In the OCC (Ortony et al. 1988) and Frijda (1993) models of emotion, appraisal matches the experience of an agent against its goals, standards, preferences and other concerns. The results of this matching give emotional events their positive or negative feeling or weight, called affect, and can also place this affective response in context.

SEU (Subjective Expected Utility Theory): Subjective expected utility theory (Simon 1983) holds that a rational agent should attempt to maximize its reward by choosing the action with the highest expected utility — effectively, the sum of the rewards of the outcomes discounted by the probabilities of their occurrence.

Concern: In Frijda’s (1986) model of emotion, concerns correspond to the needs, preferences and drives of an agent – things that “matter” and can trigger changes to the emotional state of the agent.

OCC Model of Emotion: Ortony, Clore and Collins’s (Ortony et al. 1988) model of emotion is a widely used model of emotion that states that the strength of a given emotion primarily depends on the events, agents, or objects in the environment of the agent exhibiting the emotion. A large number of researchers have employed the OCC model to generate emotions for their embodied characters. The model specifies about 22 emotion categories and consists of five processes that define the complete system that characters follow from the initial categorization of an event to the resulting behavior of the character. These processes are namely a) classifying the event, action or object encountered, b) quantifying the intensity of affected emotions, c) interaction of the newly generated emotion with existing emotions, d) mapping the emotional state to an emotional expression and e) expressing the emotional state.

Case-Based Reasoning: Case-based reasoning (Kolodner 1993) is a reasoning architecture that stores experiences with lessons learned as cases in a case library and solves problems by retrieving the case most similar to the current situation, adapting it for reuse, and retaining new solutions once they have been applied. Case-based reasoning is also a pervasive behavior in everyday human problem solving.

MDP (Markov Decision Processes): Markov decision processes provide a mathematical framework for modeling decision-making characterized by a set of states where in each state there are several actions from which the decision maker must choose and transitions to a new state at time t + 1 from time t are only dependent on the current state and independent of all previous states. MDPs are useful for studying a wide range of optimization problems solved via dynamic programming and reinforcement learning.

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Editorial Advisory Board
Table of Contents
Craig DeLancey
Jordi Vallverdú, David Casacuberta
Chapter 1
Oscar Deniz, Javier Lorenzo, Mario Hernández, Modesto Castrillón
Social intelligence seems to obviously require emotions. People have emotions, recognize them in others and also express them. A wealth of... Sample PDF
Emotional Modeling in an Interactive Robotic Head
Chapter 2
Cyril Laurier, Perfecto Herrera
Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling... Sample PDF
Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines
Chapter 3
Christoph Bartneck, Michael J. Lyons
The human face plays a central role in most forms of natural human interaction so we may expect that computational methods for analysis of facial... Sample PDF
Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble
Chapter 4
Sajal Chandra Banik, Keigo Watanabe, Maki K. Habib, Kiyotaka Izumi
Multi-robot team work is necessary for complex tasks which cannot be performed by a single robot. To get the required performance and reliability... Sample PDF
Multirobot Team Work with Benevolent Characters: The Roles of Emotions
Chapter 5
Matthias Scheutz, Paul Schermerhorn
Effective decision-making under real-world conditions can be very difficult as purely rational methods of decision-making are often not feasible or... Sample PDF
Affective Goal and Task Selection for Social Robots
Chapter 6
Christopher P. Lee-Johnson, Dale A. Carnegie
The hypothesis that artificial emotion-like mechanisms can improve the adaptive performance of robots and intelligent systems has gained... Sample PDF
Robotic Emotions: Navigation with Feeling
Chapter 7
C. Gros
All self-active living beings need to solve the motivational problem—the question of what to do at any moment of their life. For humans and... Sample PDF
Emotions, Diffusive Emotional Control and the Motivational Problem for Autonomous Cognitive Systems
Chapter 8
Bruce J. MacLennan
This chapter addresses the “Hard Problem” of consciousness in the context of robot emotions. The Hard Problem, as defined by Chalmers, refers to the... Sample PDF
Robots React, but Can They Feel?
Chapter 9
Mercedes García-Ordaz, Rocío Carrasco-Carrasco, Francisco José Martínez-López
It is contended here that the emotional elements and features of human reasoning should be taken into account when designing the personality of... Sample PDF
Personality and Emotions in Robotics from the Gender Perspective
Chapter 10
Antoni Gomila, Alberto Amengual
In this chapter we raise some of the moral issues involved in the current development of robotic autonomous agents. Starting from the connection... Sample PDF
Moral Emotions for Autonomous Agents
Chapter 11
Pietro Cipresso, Jean-Marie Dembele, Marco Villamira
In this work, we present an analytical model of hyper-inflated economies and develop a computational model that permits us to consider expectations... Sample PDF
An Emotional Perspective for Agent-Based Computational Economics
Chapter 12
Michel Aubé
The Commitment Theory of Emotions is issued from a careful scrutiny of emotional behavior in humans and animals, as reported in the literature on... Sample PDF
Unfolding Commitments Management: A Systemic View of Emotions
Chapter 13
Sigerist J. Rodríguez, Pilar Herrero, Olinto J. Rodríguez
Today, realism and coherence are highly searched qualities in agent’s behavior; but these qualities cannot be achieved completely without... Sample PDF
A Cognitive Appraisal Based Approach for Emotional Representation
Chapter 14
Clément Raïevsky, François Michaud
Emotion plays several important roles in the cognition of human beings and other life forms, and is therefore a legitimate inspiration for providing... Sample PDF
Emotion Generation Based on a Mismatch Theory of Emotions for Situated Agents
Chapter 15
Artificial Surprise  (pages 267-291)
Luis Macedo, Amilcar Cardoso, Rainer Reisenzein, Emiliano Lorini
This chapter reviews research on computational models of surprise. Part 1 begins with a description of the phenomenon of surprise in humans, reviews... Sample PDF
Artificial Surprise
Chapter 16
Tom Adi
A new theory of emotions is derived from the semantics of the language of emotions. The sound structures of 36 Old Arabic word roots that express... Sample PDF
A Theory of Emotions Based on Natural Language Semantics
Chapter 17
Huma Shah, Kevin Warwick
The Turing Test, originally configured as a game for a human to distinguish between an unseen and unheard man and woman, through a text-based... Sample PDF
Emotion in the Turing Test: A Downward Trend for Machines in Recent Loebner Prizes
Chapter 18
Félix Francisco Ramos Corchado, Héctor Rafael Orozco Aguirre, Luis Alfonso Razo Ruvalcaba
Emotions play an essential role in the cognitive processes of an avatar and are a crucial element for modeling its perception, learning, decision... Sample PDF
Artificial Emotional Intelligence in Virtual Creatures
Chapter 19
Sarantos I. Psycharis
In our study we collected data with respect to cognitive variables (learning outcome), metacognitive indicators (knowledge about cognition and... Sample PDF
Physics and Cognitive-Emotional-Metacognitive Variables: Learning Performance in the Environment of CTAT
Chapter 20
Anthony G. Francis Jr., Manish Mehta, Ashwin Ram
Believable agents designed for long-term interaction with human users need to adapt to them in a way which appears emotionally plausible while... Sample PDF
Emotional Memory and Adaptive Personalities
Chapter 21
Dorel Gorga, Daniel K. Schneider
The purpose of this contribution is to discuss conceptual issues and challenges related to the integration of emotional agents in the design of... Sample PDF
Computer-Based Learning Environments with Emotional Agents
Chapter 22
Emotional Ambient Media  (pages 443-459)
Artur Lugmayr, Tillmann Dorsch, Pabo Roman Humanes
The “medium is the message”: nowadays the medium as such is non-distinguishable from its presentation environment. However, what is the medium in an... Sample PDF
Emotional Ambient Media
Chapter 23
Jordi Vallverdú, David Casacuberta
During the previous stage of our research we developed a computer simulation (called ‘The Panic Room’ or, more simply, ‘TPR’) dealing with synthetic... Sample PDF
Modelling Hardwired Synthetic Emotions: TPR 2.0
Chapter 24
Cecile K.M. Crutzen, Hans-Werner Hein
A vision of future daily life is explored in Ambient Intelligence (AmI). It follows the assumption that information technology should disappear into... Sample PDF
Invisibility and Visibility: The Shadows of Artificial Intelligence
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