21,100 research outputs found
Toward behavioural innovation economics â Heuristics and biases in choice under novelty
A framework for âbehavioural innovation economicsâ is proposed here as a synthesis of behavioural economics and innovation economics in the specific context of choice under novelty. We seek to apply the heuristics and biases framework of behavioural economics to the study of the innovation process in order to map and analyze systematic choice failures in the innovation process. We elaborate the distinction between choice under uncertainty and choice under novelty, as well as drawing out the âefficient innovation hypothesisâ implicit in most behavioural models of innovation. The subject domain of a research program for behavioural innovation economics is then briefly outlined in terms of a catalogue of characteristic ways in which choice under novelty renders innovation processes subject to failure.
Cognitive networks: brains, internet, and civilizations
In this short essay, we discuss some basic features of cognitive activity at
several different space-time scales: from neural networks in the brain to
civilizations. One motivation for such comparative study is its heuristic
value. Attempts to better understand the functioning of "wetware" involved in
cognitive activities of central nervous system by comparing it with a computing
device have a long tradition. We suggest that comparison with Internet might be
more adequate. We briefly touch upon such subjects as encoding, compression,
and Saussurean trichotomy langue/langage/parole in various environments.Comment: 16 page
Knowledge Transfer Between Robots with Similar Dynamics for High-Accuracy Impromptu Trajectory Tracking
In this paper, we propose an online learning approach that enables the
inverse dynamics model learned for a source robot to be transferred to a target
robot (e.g., from one quadrotor to another quadrotor with different mass or
aerodynamic properties). The goal is to leverage knowledge from the source
robot such that the target robot achieves high-accuracy trajectory tracking on
arbitrary trajectories from the first attempt with minimal data recollection
and training. Most existing approaches for multi-robot knowledge transfer are
based on post-analysis of datasets collected from both robots. In this work, we
study the feasibility of impromptu transfer of models across robots by learning
an error prediction module online. In particular, we analytically derive the
form of the mapping to be learned by the online module for exact tracking,
propose an approach for characterizing similarity between robots, and use these
results to analyze the stability of the overall system. The proposed approach
is illustrated in simulation and verified experimentally on two different
quadrotors performing impromptu trajectory tracking tasks, where the quadrotors
are required to accurately track arbitrary hand-drawn trajectories from the
first attempt.Comment: European Control Conference (ECC) 201
Epistemic virtues, metavirtues, and computational complexity
I argue that considerations about computational complexity show that all finite agents need characteristics like those that have been called epistemic virtues. The necessity of these virtues follows in part from the nonexistence of shortcuts, or efficient ways of finding shortcuts, to cognitively expensive routines. It follows that agents must possess the capacities â metavirtues âof developing in advance the cognitive virtues they will need when time and memory are at a premium
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
An experimental analysis of bounded rationality: Applying insights from behavioral economics to information systems
The paradigm of bounded rationality considers the limited ability of individuals to make consistent and rational choices. Due to the scarcity of research on this phenomenon in information systems, we conducted an experimental study investigating decision-making regarding risk preferences and social preferences. Moreover, we explored the stability of these preferences under different conditions and uncovered the role of information retrieval in individual decision-making. We find that although individuals are generally risk-averse and egoistic, none of these preferences is stable under the conditions tested which provides indices of boundedly rational decision-making. Although the information retrieved by participants generally allows to infer their preferences, the increasing amount and complexity of this information again often results in boundedly rational behavior.bounded rationality, experimental design, information retrieval, stability of attitudes and behavior, cognitive tracing, behavioral economics, behavioral information systems
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