Information Theory

We develop and apply several novel methods quantifying dynamic multi-agent team interactions. These interactions are detected information-theoretically and captured in two ways: via (i) directed networks (interaction diagrams) representing significant coupled dynamics between pairs of agents, and (ii) state-space plots (coherence diagrams) showing coherent structures in Shannon information dynamics. This model-free analysis relates, on the one hand, the information transfer to responsiveness of the agents and the team, and, on the other hand, the information storage within the team to the teamʼs rigidity and lack of tactical flexibility. The resultant interaction and coherence diagrams reveal implicit interactions, across teams, that may be spatially long-range. The analysis was verified with a statistically significant number of experiments (using simulated football games, produced during RoboCup 2D Simulation League matches), identifying the zones of the most intense competition, the extent and types of interactions, and the correlation between the strength of specific interactions and the results of the matches.

The now taken-for-granted notion that data lead to information, which leads to knowledge, which in turn leads to wisdom was first specified in detail by R. L. Ackoff in 1988. The Data-Information-Knowledge-Wisdom hierarchy is based on filtration, reduction, and transformation. Besides being causal and hierarchical, the scheme is pyramidal, in that data are plentiful while wisdom is almost nonexistent. Ackoff’s formula linking these terms together this way permits us to ask what the opposite of knowledge is and whether analogous principles of hierarchy, process, and pyramiding apply to it. The inversion of the Data- Information-Knowledge-Wisdom hierarchy produces a series of opposing terms (including misinformation, error, ignorance, and stupidity) but not exactly a chain or a pyramid. Examining the connections between these phenomena contributes to our understanding of the contours and limits of knowledge.

A prior study of a congregation in Winter Haven, Florida revealed an overlap in perceived, ideal qualities of clergy and lay leaders of the church. However, these qualities were limited to exclusively shepherding and teaching roles. Through preaching a 5-week sermon series, this project began to shape a vision of shared ministry and leadership in this local church among clergy and laity alike. The series used the APEST model of Ephesians 4, taken from the missional hermeneutic of Alan Hirsch. The project assessed the emergence of an inchoate understanding of the missional imperative through ethnographic data, gathered in a sermon roundtable, and surveys collected congregationally.

The view that computers are information processors is commonplace. They are used, for the most part successfully, throughout our society, as reliable links in the transmission of information and knowledge. Yet the formulation of a precise, qualitative conception of information and a theory of the transmission of information has proved elusive, despite the many other successes of computer science. The authors set out the motivation for and a skeleton of a new mathematical model of information flow, one that is compatible with less than perfect flow

This dissertation presents a mathematically informed, cultural-materialist interpretation of a classically romantic literary-theoretic thesis: that a work of literature can aesthetically communicate an ineffably complex holistic understanding of the real world, which we might call the work's `aesthetic meaning.' Drawing on a generalization of `deep learning' ("artificial intuition") systems and on elementary algorithmic information theory, we describe a kind or aspect of aesthetic meaning—`ambient meaning'—that may have a special resonance with Modernist and avant-garde approaches to aesthetic meaning, as well as with the concepts of aesthetically sophisticated cultural-materialist literary theory of the kind that critics like Sianne Ngai or Raymond Williams practice, sometimes understood as 'affect studies.'

Abstract. One hundred years removed from AA Markov's development of his chains, we take stock of the field he generated and the mathematical impression he left. As a tribute to Markov, we present what we consider to be the five greatest applications of Markov chains ...

To behave in an adaptive way an animal must refer to information. Consider what happens when a motorist comes to traffic lights at red. The motorist usually stops. Stopping avoids the high risk of damage and injury at the cost of one or two minutes. So stopping at red traffic lights is the best way for the motorist to behave.

Lim and Leek (2012) presented a formalization of information along object contours, which they argued was an alternative to the approach taken in our article (Feldman & Singh, 2005). Here, we summarize the 2 approaches, showing that--notwithstanding Lim and Leek's (2012) critical rhetoric--their approach is substantially identical to ours, except for the technical details of the formalism. Following the logic of our article point by point, Lim and Leek (a) defined probabilistic expectations about the geometry of smooth contours (which they based on differential contour geometry, while we used a discrete approximation--the only essential difference in their approach), (b) assumed that information along the contour was proportional to the negative logarithm of probability, following standard information theory, and then (c) extended this formulation to closed contours. We analyze what they described as errors in our approach, all of which rest on mathematical misunderstandings or ...

arXiv:cs/0612076v1 [cs.IT] 15 Dec 2006 SUBMITTED TO IEEE TRANSACTIONS ON INFORMATION THEORY 1 A New Approach for Capacity Analysis of Large DimensionalMulti-Antenna Channels W. Hachem(∗), O. Khorunzhiy, Ph. Loubaton, J. Najim and L. Pastur ...

In this paper we give lower bounds for the minimum distance of evaluation codes constructed from complete intersections in toric varieties. This generalizes the results of Gold-Little-Schenck and Ballico-Fontanari who considered evaluation codes on complete intersections in the projective space.

This paper describes the development of a pedagogy that aims to engage architecture students in principles of mechanical computation and to develop critical thinking on how information and computation can be manifested and performed tectonically. I pose the question: Can we create architectures that compute?

In the present review we analyse the key features of cells, seen fundamentally as information processing machines. Even though the comparison between cells and machines or cells and computers provides a powerful tool for understanding how information is stored and processed by the cellular machinery, a series of misleading and simplistic assumptions are critically reviewed. Moreover, the seminal studies on understanding and artificially recreating the neuronal structure are analysed, both for exploiting its powerful computational abilities in information processing devices and for providing medical solutions to neurodegenerative diseases, neurological trauma and neuroprosthetics.

In many packet-based communication systems such as TCP/IP-based systems, packets are communicated over a noisy physical layer (a channel), and if a packet cannot be decoded correctly, then the transport layer retransmits it. Of course, retransmissions consume significant resources and their use should be limited. However, decreasing the likelihood of retransmission requires to encode the packets with strong channel codes in the physical layer, which also requires additional channel resources. In this paper, we study the cross-layer tradeoff between coding and packet retransmissions, and optimize over the total channel resource consumption. We show that as the packet length k increases, the redundancy r beyond the k/C channel uses implied by Shannon's channel capacity C is Theta(radickln(k)) extra channel uses. Moreover, as k increases we must use stronger channel codes. We then apply these results to universal coding over a piecewise memoryless channel with transitions between unknown i.i.d. statistics. Our constructive universal algorithm has redundancy r=O(k2/3radicln(k)) using packets of polynomially increasing lengths while accounting for possible packet drops caused by transitions in the statistics.