295 research outputs found
Complex Networks
Introduction to the Special Issue on Complex Networks, Artificial Life
journal.Comment: 7 pages, in pres
Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making
While game theory has been transformative for decision-making, the
assumptions made can be overly restrictive in certain instances. In this work,
we focus on some of the assumptions underlying rationality such as mutual
consistency and best response, and consider ways to relax these assumptions
using concepts from level- reasoning and quantal response equilibrium (QRE)
respectively. Specifically, we provide an information-theoretic two-parameter
model that can relax both mutual consistency and best response, but can recover
approximations of level-, QRE, or typical Nash equilibrium behaviour in the
limiting cases. The proposed Quantal Hierarchy model is based on a recursive
form of the variational free energy principle, representing self-referential
games as (pseudo) sequential decisions. Bounds in player processing abilities
are captured as information costs, where future chains of reasoning are
discounted, implying a hierarchy of players where lower-level players have
fewer processing resources. We demonstrate the applicability of the proposed
model to several canonical economic games.Comment: 36 pages, 15 figure
An Ansatz for undecidable computation in RNA-world automata
In this Ansatz we consider theoretical constructions of RNA polymers into
automata, a form of computational structure. The basis for transitions in our
automata are plausible RNA-world enzymes that may perform ligation or cleavage.
Limited to these operations, we construct RNA automata of increasing
complexity; from the Finite Automaton (RNA-FA) to the Turing Machine equivalent
2-stack PDA (RNA-2PDA) and the universal RNA-UPDA. For each automaton we show
how the enzymatic reactions match the logical operations of the RNA automaton,
and describe how biological exploration of the corresponding evolutionary space
is facilitated by the efficient arrangement of RNA polymers into a
computational structure. A critical theme of the Ansatz is the self-reference
in RNA automata configurations which exploits the program-data duality but
results in undecidable computation. We describe how undecidable computation is
exemplified in the self-referential Liar paradox that places a boundary on a
logical system, and by construction, any RNA automata. We argue that an
expansion of the evolutionary space for RNA-2PDA automata can be interpreted as
a hierarchical resolution of the undecidable computation by a meta-system (akin
to Turing's oracle), in a continual process analogous to Turing's ordinal
logics and Post's extensible recursively generated logics. On this basis, we
put forward the hypothesis that the resolution of undecidable configurations in
RNA-world automata represents a mechanism for novelty generation in the
evolutionary space, and propose avenues for future investigation of biological
automata
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