• Corpus ID: 1070422

Toward a Model of Mind as a Laissez-Faire Economy of Idiots

@inproceedings{Baum1996TowardAM,
  title={Toward a Model of Mind as a Laissez-Faire Economy of Idiots},
  author={Eric B. Baum},
  booktitle={ICML},
  year={1996}
}
  • E. Baum
  • Published in ICML 3 July 1996
  • Economics
A learning machine called \The Hayek Machine" is proposed and tested on a simulated Blocks World planning problem. [] Key Method First, the market price learns to estimate Hayek's future reward from using a given agent. Second, the market automatically selects the agent with highest estimate to act next. Third, new agents can enter the market if and only if they have greater expected utility than direct competitors. Hayek learns by gradual accretion of useful agents and elimination of poor ones,and by…
Toward a Model of Intelligence as an Economy ofIdiots
A market-based algorithm is presented which autonomously apportions complex tasks to multiple cooperating agents giving each agent the motivation of improving performance of the whole system. A
Toward a Model of Intelligence as an Economy of Agents
  • E. Baum
  • Computer Science
    Machine Learning
  • 2004
A market-based algorithm is presented which autonomously apportions complex tasks to multiple cooperating agents giving each agent the motivation of improving performance of the whole system. A
A Survey of Collective Intelligence
TLDR
COIN science is presented, which has already resulted in successes in artificial domains, in particular in packet-routing, the leader-follower problem, and in variants of Arthur's "El Farol bar problem".
An Introduction to Collective Intelligence
This paper surveys the emerging science of how to design a “COllective INtelligence” (COIN). A COIN is a large multi-agent system where: i) There is little to no centralized communication or control.
Evolution of Cooperative Problem Solving in an Artificial Economy
TLDR
It is found empirically that starting from programs that are random computer code, the economy can develop systems that solve hard problems and learns to solve almost all random Blocks World problems with goal stacks that are 200 blocks high.
Learning to Play Using Low-Complexity Rule-Based Policies: Illustrations through Ms. Pac-Man
TLDR
This article defines a set of high-level observation and action modules, from which rule-based policies are constructed automatically, and argues that learning is successful mainly because policies may apply concurrent actions and thus the policy space is sufficiently rich.
The Society of Mind Requires an Economy of Mind
A society of mind will require an economy of mind, that is multi-agent systems (MAS) that meet a requirement for the adaptive allocation and reallocation of scarce resources will need to use a
The World-Wide-Mind: Draft Proposal
TLDR
This paper shows how previous models of mind where competition took place between extremely incompatible components, and where the mind could survive communications failure with or even complete loss of a number of such components are the type of models needed in the WWM.
Learning Action Strategies for Planning Domains
Applying probabilistic rules to relational worlds
TLDR
This work attempts to characterize an approach to planning in a relational domain when the world model is represented as a potentially incomplete and/or redundant set of uncertain rules.
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