Is There an Intelligent Agent in Your Future?

Imagine that you are lucky enough to find some free time in your schedule, and so you decide to take a trip. What do you do? If you’re like most people, you contact a travel agent to arrange the details. You describe your needs (where you want to go and when), the constraints that you need to impose (how much you are willing to spend, the hotel must provide child care) and some personal preferences (your preferred airline, you’d like to sit in an aisle seat). The travel agent, using a combination of information sources (flight schedules, hotel guides) and guided by past experiences, recommends where you might go. Once you confirm your plans, the agent generates the itinerary, books the flights and generally does all the things that you don’t want to bother with.

History of Intelligent Tutoring Systems

Intelligent tutors
fall under a general category of “adaptive-response” teaching systems.
The earliest adaptive response systems were developed in the 1960’s, and
sometimes referred to as programmed learning systems. Generally,
intelligent tutors have the following components:

Article mentions that not a whole lot has changed since 1990 with regard to design of intelligent tutors despite great changes in technology and delivery choices. I’m also amazed at how little I’m finding about intelligent instructional agents in the last few years. Most literature seems to be from mid- to late-90’s. There is a lot of recent stuff on AI (very technical) but very little on the theory of instructional intelligent agent design (esp. in light of new technolgies). Why did this “burn out?”

Is it an Agent or just a Program?: A Taxonomy for Autonomous Agents

“The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a natural kinds taxonomy of autonomous agents, and discuss possibilities for further classification. Finally, we discuss subagents and multiagent systems.”

An overview of different intellient agent definitions. Let’s make sure we’re all talking about the same think. . .

Lifelong Learning: The Postmodern Condition of Education?

” Abstract: In this paper, we argue that moves to reconfigure the education of adults as a dimension of lifelong learning signify a postmodern condition of education. In particular, we suggest that lifelong learning contributes to performativity and a loss of mastery, while at the same time opening up different possibilities for adult learners. This poses complex challenges to adult educators.”

“Abstract. The availability of the emote
modality, combined with social responses to object
and room-persistence in MUDs, creates a more
structured and flexible communication environment
than is found in other single modality
chat programs. The emote command is used for
ritual greetings and goodbyes, for back channels
during conversations, for play interactions, for
reports of activity in “real life” which might
distract a user from the conversation, and for
presentation of background information during
conversations. I discuss the status of emoted
actions as speech acts, and how their
interpretation depends on frame of reference
within the virtual world and the real world.”

E-Learning Frameworks and Tools: Is it too late? – The Director’s Cut

…”I consider what is likely to happen when the JISCís vision as promulgated in the various documents and calls supporting both the JISC E-Learning Programme and the JISC Information Environment meets the reality of e-learning infrastructures as already being built at the coalface. I suggest that because key decisions and investments are already being (or have been) made, the widespread adoption by institutions of the current generation of MLE/VLEs is in danger of creating a de facto global e-learning monoculture.”

tales of swimming upstream