7.1 Value function methods| The Dan MacKinlay stable of variably-well-consider’d enterprises
Distributed sensing, swarm sensing, adaptive social learning, multi-agent adaptation, iterated game theory with learning etc| The Dan MacKinlay stable of variably-well-consider’d enterprises
Iterated and evolutionary game theory| The Dan MacKinlay stable of variably-well-consider’d enterprises
Getting ready for the grown-ups to arrive| The Dan MacKinlay stable of variably-well-consider’d enterprises
Microeconomic of compute| The Dan MacKinlay stable of variably-well-consider’d enterprises
Figure 1 Learning agents in a multi-agent system which account for and/or exploit the fact that other agents are learning too. This is one way of formalising the idea of theory of mind. Learning with theory of mind works out nicely for reinforcement learning, in e.g. opponent shaping, and may be an important tool for understanding AI agency and AI alignment, as well as aligning more general human systems. Other interesting things might arise from a good theory of other-aware learning, such ...| The Dan MacKinlay stable of variably-well-consider’d enterprises
Figure 1 1 Incoming Inside the U.K.’s Bold Experiment in AI Safety | TIME Governing with AI | Justin Bullock Deep atheism and AI risk - Joe Carlsmith Wong and Bartlett (2022) we hypothesize that once a planetary civilization transitions into a state that can be described as one virtually connected global city, it will face an ‘asymptotic burnout’, an ultimate crisis where the singularity-interval time scale becomes smaller than the.env time scale of innovation. If a civilization develo...| The Dan MacKinlay stable of variably-well-consider’d enterprises