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20
Intelligence by Design: Principles of Modularity and Coordination for Engineering Complex Adaptive Agents
, 2001
"... All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. T ..."
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Cited by 81 (27 self)
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All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation
Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... The existence of emotion and cognition as two interacting systems, both with important roles in decision-making, has been recently advocated by neurophysiological research (LeDoux, 1998, Damasio, 1994). Following that idea, this paper presents the ALEC agent architecture which has both emotive an ..."
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Cited by 26 (0 self)
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The existence of emotion and cognition as two interacting systems, both with important roles in decision-making, has been recently advocated by neurophysiological research (LeDoux, 1998, Damasio, 1994). Following that idea, this paper presents the ALEC agent architecture which has both emotive and cognitive learning, as well as emotive and cognitive decision-making capabilities to adapt to real-world environments. These two learning mechanisms embody very different properties which can be related to those of natural emotion and cognition systems. The reported
Robot Learning Driven by Emotions
, 2001
"... The adaptive value of emotions in nature indicates that they might also be useful in artificial creatures. Experiments were carried out to investigate this hypothesis in a simulated learning robot. For this purpose, a non-symbolic emotion model was developed that takes the form of a recurrent art ..."
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Cited by 19 (3 self)
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The adaptive value of emotions in nature indicates that they might also be useful in artificial creatures. Experiments were carried out to investigate this hypothesis in a simulated learning robot. For this purpose, a non-symbolic emotion model was developed that takes the form of a recurrent artificial neural network where emotions both depend on and influence the perception of the state of the world. This emotion
Emotion-triggered Learning in Autonomous Robot Control
- CYBERNETICS AND SYSTEMS
, 2001
"... The fact that emotions are considered to be essential to human reasoning suggests that they might play an important role in autonomous robots as well. In particular, the decision of when to interrupt on-going behaviour is often associated with emotions in natural systems. The question under exami ..."
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Cited by 13 (3 self)
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The fact that emotions are considered to be essential to human reasoning suggests that they might play an important role in autonomous robots as well. In particular, the decision of when to interrupt on-going behaviour is often associated with emotions in natural systems. The question under examination here is whether this role of emotions can be useful for a robot which adapts to its environment. For this purpose, an emotion model was developed and integrated in a reinforcement learning framework. Robot experiments were done to test an emotion-dependent mechanism for the automatic detection of the relevant events of a learning task, against more traditional approaches. Experimental results are presented that conrm that emotions can be useful in this role, specically by improving the efficiency of the learning algorithm.
The study of sequential and hierarchical organisation of behaviour via artificial mechanisms of action selection
- University of Edinburgh
, 2000
"... One of the defining features of intelligent behaviour is the ordering of individual expressed actions into coherent, apparently rational patterns. Psychology has long assumed that hierarchical and sequential structures internal to the intelligent agent underlie this expression. Recently these assump ..."
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Cited by 13 (7 self)
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One of the defining features of intelligent behaviour is the ordering of individual expressed actions into coherent, apparently rational patterns. Psychology has long assumed that hierarchical and sequential structures internal to the intelligent agent underlie this expression. Recently these assumptions have been challenged by claims that behaviour controlled by such structures is necessarily rigid, brittle, and incapable of reacting quickly and opportunistically to changes in the environment (Hendriks-Jansen 1996, Goldfield 1995, Brooks 1991a). This dissertation is intended to support the hypothesis that sequential and hierarchical structures are necessary to intelligent behaviour, and to refute the above claims of their impracticality. Three forms of supporting evidence are provided: • a demonstration in the form of experimental results in two domains that structured intelligence can lead to robust and reactive behaviour, • a review of recent research results and paradigmatic trends within artificial intelligence, and • a similar examination of related research in natural intelligence.
Making modularity work: Combining memory systems and intelligent processes in a dialog agent
- AISB’00 Symposium on Designing a Functioning Mind
, 2000
"... One of the greatest obstacles to designing a mind is the complexity of integrating different process types, time frames and representational structures. This paper describes a methodology for addressing this obstacle, Behavior Oriented Designed (BOD), and explains it in the context of creating an ag ..."
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Cited by 10 (9 self)
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One of the greatest obstacles to designing a mind is the complexity of integrating different process types, time frames and representational structures. This paper describes a methodology for addressing this obstacle, Behavior Oriented Designed (BOD), and explains it in the context of creating an agent capable of natural language dialogue. 1
A biologically inspired architecture for an autonomous and social robot,” Autonomous Mental Development
- IEEE Transactions on
, 2011
"... Abstract-Lately, lots of effort has been put into the construction of robots able to live among humans. This fact has favored the development of personal or social robots, which are expected to behave in a natural way. This implies that these robots could meet certain requirements, for example: to ..."
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Cited by 6 (0 self)
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Abstract-Lately, lots of effort has been put into the construction of robots able to live among humans. This fact has favored the development of personal or social robots, which are expected to behave in a natural way. This implies that these robots could meet certain requirements, for example: to be able to decide their own actions (autonomy), to be able to make deliberative plans (reasoning), or to be able to have an emotional behavior in order to facilitate human-robot interaction. In this paper, the authors present a bio-inspired control architecture for an autonomous and social robot, which tries to accomplish some of these features. In order to develop this new architecture, authors have used as a base a prior hybrid control architecture (AD) that is also biologically inspired. Nevertheless, in the later, the task to be accomplished at each moment is determined by a fix sequence processed by the Main Sequencer. Therefore, the Main Sequencer of the architecture coordinates the previously programmed sequence of skills that must be executed. In the new architecture, the Main Sequencer is substituted by a decision making system based on drives, motivations, emotions, and self-learning, which decides the proper action at every moment according to robot's state. Consequently, the robot improves its autonomy since the added decision making system will determine the goal and consequently the skills to be executed. A basic version of this new architecture has been implemented on a real robotic platform. Some experiments are shown at the end of the paper.
Simplifying the design of human-like behaviour: Emotions as durative dynamic state for action selection
- International Journal of Synthetic Emotions
, 2009
"... Human intelligence requires decades of full-time training before it can be reliably utilised in modern economies. In contrast, AI agents must be made reliable but interesting in relatively short order. Realistic emotion representations are one way to ensure that even relatively simple specifications ..."
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Cited by 5 (4 self)
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Human intelligence requires decades of full-time training before it can be reliably utilised in modern economies. In contrast, AI agents must be made reliable but interesting in relatively short order. Realistic emotion representations are one way to ensure that even relatively simple specifications of agent behaviour will be expressed with engaging variation, and that social and temporal contexts can be tracked and responded to appropriately. We describe here a representation system for maintaining an interacting set of durative states in order to replicate emotional control. Our model, the Dynamic Emotion Representation (DER) integrates emotional responses and keeps track of emotion intensities changing over time. The developer can specify an interacting network of emotional states with appropriate onsets, sustains and decays. The levels of these states can be used as input for action selection, including emotional expression. We present both a general representational framework and a specific instance of a DER network constructed for a virtual character. The character’s DER uses three types of emotional state as classified by duration timescales, in keeping with current emotional theory. We demonstrate the system with a virtual actor. We also demonstrate how even a simplified version of this representation can improve goal arbitration in autonomous agents. 1
Improved Animal-Like Maintenance of Homeostatic Goals via Flexible Latching ∗
"... Artificial cognitive systems sometimes neglect the impact on action selection of natural durativestate mechanisms like emotions and drives. These chemically-regulated motivation systems assist natural action selection through temporarily focusing an agent’s behavioural attention on particular proble ..."
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Cited by 3 (3 self)
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Artificial cognitive systems sometimes neglect the impact on action selection of natural durativestate mechanisms like emotions and drives. These chemically-regulated motivation systems assist natural action selection through temporarily focusing an agent’s behavioural attention on particular problems. This can improve efficiency by avoiding dithering, but taken to extremes can be inefficient in ways that seem cognitively improbable for mammal-level intelligence. This article demonstrates a flexible latching method that provides appraisal-based sensitivity to interruption, allowing reassessment of the current focus of attention. This drastically improves efficiency in handling multiple competing goals at the cost of a surprisingly small amount of extra cognitive complexity.
The impact of durative state on action selection
- Proceedings of the AAAI Spring Symposium on Emotion, Personality, and Social Behavior
"... Chemical / hormonal diffusion is the phylogenetically oldest form of biological action selection. In this paper we argue its persistence in higher animals is a consequence of its utility in solving problems of dithering between high-level goals. Chemical state underlying emotions and drives provides ..."
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Cited by 2 (2 self)
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Chemical / hormonal diffusion is the phylogenetically oldest form of biological action selection. In this paper we argue its persistence in higher animals is a consequence of its utility in solving problems of dithering between high-level goals. Chemical state underlying emotions and drives provides greater persistence more easily than the electrical action potential systems underlying the fine details of action sequencing, while also providing periodicity and transience not easily afforded in longer-term learning systems such as synaptic plasticity. We argue that artificial real-time autonomous systems require similar systems, and review our own efforts and approaches to providing these.
