Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP
Path: utzoo!utgpu!water!watnot!watmath!clyde!cbatt!ucbvax!atc.bendix.com!DON
From: DON@atc.bendix.com.UUCP
Newsgroups: mod.ai
Subject: Request for information
Message-ID: <8703050610.AA20900@ucbvax.Berkeley.EDU>
Date: Mon, 2-Mar-87 12:18:00 EST
Article-I.D.: ucbvax.8703050610.AA20900
Posted: Mon Mar  2 12:18:00 1987
Date-Received: Fri, 6-Mar-87 21:31:26 EST
Sender: daemon@ucbvax.BERKELEY.EDU
Distribution: world
Organization: The ARPA Internet
Lines: 27
Approved: ailist@sri-stripe.arpa

I'm looking for references or discussions on associating
observations with agents in multi-agent domains.  My concern
is not so much with determining the goodness of association
as it is with controlling which associations are explored
(i.e. controlling the search).

In particular, consider a domain in which the particular agents
are not known but the general types and proportions of each type
are known. There is a fixed set of sensors for observing these
agents. None of the sensors provides absolute identification nor
continuous observation.  There is some knowledge about the
typical behaviors of the different types of agents.  The
reasoner's problem is, when presented with a new sensor report,
to determine whether to associate the report with a new agent or
with a previously observed agent.  The problem quickly becomes
one of controlling the search of previously observed agents
in order to see which are most likely to be associated with
the new report.

I have some ideas about the search, but I'd like to see other
published ideas or talk to those wiser than I before I expose
myself.  Thank you for any consideration.

Don Mitchell			Don@atc.bendix.com or
Bendix Aero. Tech. Ctr.		Don%atc.bendix.com@relay.cs.net
9140 Old Annapolis Rd.		(301)964-4156
Columbia, MD  21045