Artificial Intelligence

Recommended
Randy Davis (1998): "What Are Intelligence? And Why?" pdf
(A reasonably good synthesis of a lot of research on intelligence in computers, humans, and non-human animals. Skip the part on evolution, though.)
Yarden Katz (2012): "Noam Chomsky on Where Artificial Intelligence Went Wrong" link
(In which the number of good points about AI Noam Chomsky raises is far less than the number of interesting anecdotes he tells)
Cosma Shalizi (2007): "g, a Statistical Myth" link
(In which it is argued that the factor analysis behind IQ does not provide evidence for a single causal factor that explains correlated performance on a variety of tasks)

To Read
Langton (1986): "Studying artificial life with cellular automata" link
Minsky (1974): "A Framework for Representing Knowledge" link
A. D. Wissner-Gross and C. E. Freer (2013): "Causal Entropic Forces" pdf

Automating Scientific Discovery

Bareinboim and Pearl (2013): "A General Algorithm for Deciding Transportability of Experimental Results" link

BDI Framework

Costa Pereira (2010): "An integrated possibilistic framework for goal generation in cognitive agents" link

Bounded Rationality

Alechina (2010): "Resource-bounded alternating-time temporal logic" link
Das (2006): "On Agent-Based Modeling of Complex Systems: Learning and Bounded Rationality" pdf
Genewein and Braun (2013): "Abstraction in decision-makers with limited information processing capabilities" link
Grau-Moya and Braun (2013): "Bounded Rational Decision-Making in Changing Environments" link
Ortega (2010): "A Uniﬁed Framework for Resource-Bounded Autonomous Agents Interacting with Unknown Environments" pdf
Ortega and Lee (2013): "An Adversarial Interpretation of Information-Theoretic Bounded Rationality" pdf
Varshney et al. (2011): "Categorical Decision Making by People, Committees, and Crowds" pdf

Modal Logic

Halpern and Kets (2014): "A logic for reasoning about ambiguity" link

Search

Hills et al. (2014): "Exploration versus exploitation in space, mind, and society" link

summary

This paper discusses how taking a perspective of various behavioral systems as performing search can help explain many aspects of those systems. The paper focuses on the exploration-exploitation trade-off and how it appears in various areas. The paper argues that similar search strategies are used across various modalities, including search in physical and abstract spaces. The paper provides a good review of relevant literature, including some interesting papers to look at that describe optimal search strategies. The paper also focuses heavily on how various abnormalities of individuals or groups can viewed as those entities being too extreme in terms of exploration or exploitation. From an AI perspective, the idea of cognition as search is not new, but the article synthesizes a lot of empirical and theoretical literature illustrating this idea from various areas, which is nice.

Peter M Krafft Last modified: Sat Dec 20 13:15:59 EST 2014