RETE and LP (by which I presume you mean logic programming) don’t most naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.

But the most natural metric would be performance, I would think :)

And do you mean “optimizations” by “heuristics”? Many optimizations are not heuristic, at least not in how I understand “heuristic”.

RETE and LP (by which I presume you mean logic programming) don’t most naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.

But the most natural metric would be performance, I would think :)

And do you mean “optimizations” by “heuristics”? Many optimizations are not heuristic, at least not in how I understand “heuristic”.

RETE and LP (by which I presume you mean logic programming) don’t most naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.

But the most natural metric would be performance, I would think :)

And do you mean “optimizations” by “heuristics”? Many optimizations are not heuristic, at least not in how I understand “heuristic”.

RETE and LP (by which I presume you mean logic programming) don’t most naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.

But the most natural metric would be performance, I would think :)

And do you mean “optimizations” by “heuristics”? Many optimizations are not heuristic, at least not in how I understand “heuristic”.

RETE and LP (by which I presume you mean logic programming) don’t most naturally conflate in my lexicon. The bog standard framework for LP is resolution, from Prolog and Datalog to disjunctive datalog and answer set programming.

But the most natural metric would be performance, I would think :)

And do you mean “optimizations” by “heuristics”? Many optimizations are not heuristic, at least not in how I understand “heuristic”.

I’ve recently pondered hooking up the python RETE-UL [2] implementation I’ve been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases. I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.

Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)

[1] http://aima.cs.berkeley.edu/python/logic.html
[2] http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf

I’ve recently pondered hooking up the python RETE-UL [2] implementation I’ve been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases. I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.

Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)

[1] http://aima.cs.berkeley.edu/python/logic.html
[2] http://reports-archive.adm.cs.cmu.edu/anon/1995…;

I’ve recently pondered hooking up the python RETE-UL [2] implementation I’ve been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases. I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.

Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)

[1] http://aima.cs.berkeley.edu/python/logic.html
[2] http://reports-archive.adm.cs.cmu.edu/anon/1995…;

I’ve recently pondered hooking up the python RETE-UL [2] implementation I’ve been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases. I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.

Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)

[1] http://aima.cs.berkeley.edu/python/logic.html
[2] http://reports-archive.adm.cs.cmu.edu/anon/1995…;

I’ve recently pondered hooking up the python RETE-UL [2] implementation I’ve been playing with a means to track a non-circular path through the RETE network as an alternative proof generation mechanism for large rulesets and factbases. I wonder if there is some metric for comparing the application of LP heuristics to DLP reasoning against (more traditional) resolution and tableux-based heuristics for the same KR.

Generated proofs, whether or not they are truely valuable, bring about a certain unmatchable satisfaction to a logician =)

[1] http://aima.cs.berkeley.edu/python/logic.html
[2] http://reports-archive.adm.cs.cmu.edu/anon/1995…;