Agents

General Impressions: 

Agents are an important part of gaming, and ties closely to Virtual Reality.

Agents are typically programmed characters within a game that exhibit some sort of artificial intelligence.

Better agents typically means better AI, which adds complexity and fun to a game.  Agents can model human communication, using things like non-verbal gestures, grounding speech acts, etc., to communicate with game players.
 

Lewis Johnson (below) theorizes that increased social interaction / communication skills possessed by the agents will directly relate to higher levels of learning.  (more stimulating)

"The goal is to create agents that exhibit expressiveness (the ability to convey emotions and attitudes), empathy (sensitivity to learner motivational and emotional states), and politeness (an understanding of when and how to interact in socially appropriate ways)."
 

Seems like good agents have a lot to do with human communication theory (my notes on that).


 

Lewis Johnson at ISI/USC:

Homepage for CARTE (Center for Advanced Research in Technology for Education)

CARTE focuses on developing new technology for use in training and education.

One of their main focuses / projects involves socially intelligent agents - agents in the simulation with advanced social and communication skills.  They theorize this directly increases levels of learning by the participants.

If my dissertation's independent variable has something to do with social interaction, this work would be key.

It's not just about being more stimulating, learning conversational maxims, etc. - it also has to do with NOT breaking rules of encouragement, offering the learner respect, and not criticizing same mistake over and over (leads to frustration)

Agent-oriented view of HCI:  virtual learners, teachers, other agents act together as a team where roles and responsibilities are dynamically distributed

Involves utilizing many human communication theories:  common ground, grounding, eye contact, gestures, negotiation acts, etc.

Studies show learners have different interaction styles / preferences- so virtual agents / tutors should adjust accordingly

Theoretical Framework:  Learner Motivation (4 C's:  Curiosity, Challenge, Confidence, Control) and Politeness (Brown & Levinson:  mitigating face threatening acts) and presentation of self (E. Goffman)

Traum, D. and Rickel, J. 2002. Embodied agents for multi-party dialogue in immersive virtual worlds. In Proceedings of the First international Joint Conference on Autonomous Agents and Multiagent Systems: Part 2 (Bologna, Italy, July 15 - 19, 2002). AAMAS '02. ACM Press, New York, NY, 766-773. DOI= http://doi.acm.org/10.1145/544862.544922