Search Results for author:
Found 7 papers, 1 papers with code
Strengthening Consistency Results in Modal Logic
and then shows the assumptions codified by the theory in question to be consistent with those background axioms.
Universal Agent Mixtures and the Geometry of Intelligence
Thus, if RL agent intelligence is quantified in terms of performance across environments, the weighted mixture's intelligence is the weighted average of the original agents' intelligences.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
Extending Environments To Measure Self-Reflection In Reinforcement Learning
We consider an extended notion of reinforcement learning in which the environment can simulate the agent and base its outputs on the agent's hypothetical behavior.
The Archimedean trap: Why traditional reinforcement learning will probably not yield AGI
After generalizing the Archimedean property of real numbers in such a way as to make it adaptable to non-numeric structures, we demonstrate that the real numbers cannot be used to accurately measure non-Archimedean structures.
Measuring the intelligence of an idealized mechanical knowing agent
We define a notion of the intelligence level of an idealized mechanical knowing agent.
Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents
Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense.
