Codesota · Models · SAC (state-based)UC Berkeley1 results · 1 benchmarks
Model card

SAC (state-based).

UC Berkeleyopen-source
§ 01 · Benchmarks

Every benchmark SAC (state-based) has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01MuJoCoReinforcement Learning · Continuous Controlaverage-return777.00#9/9source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 02 · Strengths by area

Where SAC (state-based) actually performs.

Reinforcement Learning
1
benchmark
avg rank #9.0
§ 04 · Related models

Other UC Berkeley models scored on Codesota.

CQL (Conservative Q-Learning)
0 results
IQL (Implicit Q-Learning)
0 results
Octo-Base
0 results
SAC
0 results
§ 05 · Sources & freshness

Where these numbers come from.

icml-2018-paper
1
result
0 of 1 rows marked verified.