Dynamic Learning Agents and Enhanced Presence on the Grid

Abstract

Human Learning on the Grid will be based on the synergies between advanced software and Human agents. These synergies will be possible to the extent that conversational protocols among Agents, human and/or artificial ones, can be adapted to the ambitious goal of dynamically generating services for human learning. In the paper we highlight how conversations may procure learning both in human and in artificial Agents. The STROBE model for communicating Agents and its current evolutions shows how an artificial Agent may "learn" dynamically (at run time) at the Data, Control and Interpreter level, in particular exemplifying the "learning by being told" modality. The enhanced telepresence research, exemplified by Buddyspace, in parallel, puts human Agents in a rich communicative context where learning effects may occur also as a "serendipitous" side effect of communication. The integration of the two streams of research will be the result of a workpackage within the E-LeGI EU Integrated Project, currently under negotiation.

Peer Conversations for e-Learning in the Grid

“…any action or thought process can involve multiple steps at different levels of abstraction); (ii) the 'Peer-to-peer' (P2P) multiple boxes in the lower right hand corner, to highlight the fact that peer group interactions (not only student-student but also teacher-teacher) are in fact fundamental to many learning scenarios, and (iii) the important caveat that any instance of Teacher T or Student S may also be viewed as an agent, and indeed may be either an artificial agent or a human agent, in an arbitrary mix (here labelled 'Teacher/agent = T/A' and 'Student/agent = S/A'. The relationships among the possible T/A and S/A dyads is explored further in [5], whereas in the rest of this paper we concentrate on the peer group interactions.…”

Movement and interaction in semantic GRIDs: dynamic service generation for Agents in the MIC* deployment environment

“…In this section we will present our vision on the synergies between MIC* , semantic GRID, agents and e-Learning as it becomes more and more clear by working in LEGE-WG and ELEGI. The dynamic generation of services by agents on the GRID was previously introduced and discussed in a few introductory papers: [12,22,10,13].…”

“…We believe that higher level services such as those emerging from semantically rich domains will require this model to co-exist with the other ones. At the moment, the only viable and generic solution for deploying services that conserve state seems for us the use of Continuations [23] within developments -such as those around the STROBE model -that adopt first class continuations in order to model easily context switching among conversational threads [13]. • 'stateless services that act upon stateful resources': These are services of an intermediate complexity -in terms of needs for state and memory -as seems to us to be the case in most of the examples offered by [4].…”

“…These acts may initially consist of those presented in the examples of WSRF: read a state variable, write a state variable. We therefore look at WS Resources as if they were a kind of agents, consisting of a quite limited dispatching capability, but controlling each an Environment in the STROBE sense where variables may be bound to any first class structure available in the model (simple and complex data, but also functions, continuations, other environments, and interpreters: [13]. 4.…”