It is true that the Rete algorithm (on which Jess is based) is built on the assumption that only a small fraction (usually quoted as 5-10%) of the knowledge base will change on each evaluation cycle. Populating the network from scratch is expensive and constantly resetting it does degrade performance quite seriously.
On the other hand, if the whole knowledge base must be constantly reevaluated, than no other algorithm will necessarily be any better. Rather than searching for other tools, you might put some work into figuring out how to preserve those parts of the KB that don't change as frequently, rather than constantly resetting. Presumably there are stationary objects and information about ownership and properties that don't change often. ________________________________ From: owner-jess-us...@sandia.gov [mailto:owner-jess-us...@sandia.gov] On Behalf Of Sam Sarjant Sent: Sunday, October 09, 2011 5:49 PM To: jess-users Subject: JESS: Using JESS for representing game states Hello, I have been using JESS for some time as a rule-system for representing states in a game (relational reinforcement learning), such that the state of the game can be represented in terms of objects. An agent uses these states and a decision making process (in this case defqueries to resolve rules in conditions -> action form). Because games are very dynamic environments, the state is constantly changing. I am currently handling this by resetting the state and reasserting the facts of the state (then running to generate any further facts that rules generate). My question is: is JESS the best rule-system to use for this task? I know JESS has the property of only generating facts once, but if the state is constantly being reset, perhaps some other system would be more effective. JESS certainly gets the job done, and I haven't really tested anything else, but I am concerned with the speed of execution, but perhaps this is simply due to the fact that I am using this relational representation. -- - Thanks, Sam Sarjant www.samsarjant.com<http://www.samsarjant.com>