Week 8

Week 8: 2006/10/16 – 2006/10/20

Motivational Beliefs, Values and Goals

Eccles, Jacquelynne S., and Allen Wigfield. “Motivational Beliefs, Values and Goals.” Annual Review of Psychology. 53 (2002): 109-132.

Eccles and Wigfied review modern theories for motivation, specifically in relation to beliefs, values, and goals. I found their sections focusing on reasons for engagement and integrating motivation and cognition especially interesting. Intrinsic motivations are a reason for engagement, motivation occurs because of interest in the activity. Eccles and Wigfield present a few theories here: self-determination theory , flow theory, and individual difference of intrinsic motivation. They also presented goal theories which they break down into ego-involved goals, maximizing positive results and minimizing negative results, and task-involved goals, mastering tasks to improve the individual. In the integrating motivation and cognition section the authors present theories about self-efficacy and self-regulation.

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Creatures: Entertainment Software Agents with Artificial Life

Grand, Stephen, and Dave Cliff. “Creatures: Entertainment Software Agents with Artificial Life.” Autonomous Agents and Multi-Agent Systems. 1.1 (1998): 39-57.

Grand and Cliff present the work done on the game Creatures where the player interacts in real-time with synthetic creatures in a virtual environment. These creatures have “artificial neural networks for sensory-motor control and learning, artificial biochemistries for energy metabolism and hormonal regulation of behavior, and both the network and the biochemistry are 'genetically' specified to allow for the possibility of evolutionary adaptation through sexual reproduction.” The paper goes on to describe how these functions work. One of the more interesting aspects is how they designed their neural network and brain model. The neural network is divided into nine lobes interconnected by synapses. Each lobe consists of neurons with similar characteristics. The brain model regulates information flow through the lobes. Though it's fairly simple in its construction and is behaviorialist, it provides a logic for how the creature processes information and chooses actions.

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Synthetic Vision and Memory for Autonomous Virtual Humans

Peters, C., and C. O'Sullivan. “ Synthetic Vision and Memory for Autonomous Virtual Humans.” Computer Graphics Forum. 21.4 (2002): 743-753.

Peters and O'Sullivan present a model that combines memory and synthetic vision to give synthetic agents realistic knowledge about the location of objects in the world. Synthetic vision consists of two modes. Distinct vision mode, which false-colors each object with a unique color which is used to look up the object in the scene database. Grouped vision mode objects are false-colored with group colors and is used for lower detail perception and only provides information for visible objects. Since it is unrealistic for memory model to store all objects an agent has come in contact with, filters have been devised to reduce the amount of information stored. The filtering process is done through different types of memory: short-term sensory memory, short-term memory, and long-term memory.

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Research problems in the use of a shallow Artificial Intelligence model of personality and emotion

Elliot, Clark. “ Research problems in the use of a shallow Artificial Intelligence model of personality and emotion.” Proc. of the 12th National Conference on Artificial Intelligence, 1994, Seattle. 9-15.

Largely this article spends less time discussing research problems and more time discussing the work being done by the author. Throughout this he does raise interesting ideas, one of them being that users want to express emotions to a computer given that the computer gives a believable illusion of comprehension. We want to anthropomorphise the computer, or the agents in the virtual environment we're interacting with.