Multiresolution vector quantization

Multiresolution source codes are data compression algorithms yielding embedded source descriptions. The decoder of a multiresolution code can build a source reproduction by decoding the embedded bit stream in part or in whole. All decoding procedures start at the beginning of the binary source description and decode some fraction of that string. Decoding a small portion of the binary string gives a low-resolution reproduction; decoding more yields a higher resolution reproduction; and so on. Multiresolution vector quantizers are block multiresolution source codes. This paper introduces algorithms for designing fixed- and variable-rate multiresolution vector quantizers. Experiments on synthetic data demonstrate performance close to the theoretical performance limit. Experiments on natural images demonstrate performance improvements of up to 8 dB over tree-structured vector quantizers. Some of the lessons learned through multiresolution vector quantizer design lend insight into the design of more sophisticated multiresolution codes

Multi-resolution VQ: parameter meaning and choice

In multi-resolution source coding, a single code is used to give an embedded data description that may be decoded at a variety of rates. Recent work in practical multi-resolution coding treats the optimal design of fixed- and variable-rate tree-structured vector quantizers for multi-resolution coding. In that work the codes are optimized for a designer-specified priority schedule over the system rates, distortions, or slopes. The method relies on a collection of parameters, which may be difficult to choose. This paper explores the meaning and choice of the multi-resolution source coding parameters

How to Build a Domesticated Fox: The Start of a Long Journey

In 1959, outside of Novosibirsk, Siberia, Dmitri Belyaev and Lyudmila Trut began what remains one of the longest-running experiments in biology. For the last 59 years they have been domesticating silver foxes and studying evolution in real time. Belyaev died in 1985, but Trut has continued to lead this experiment up to this very day. Each generation they and their team have been selecting the calmest, most prosocial-toward-humans foxes and preferentially breeding those individuals. Today they have foxes that are calmer than lap dogs, and who also look eerily dog-like—floppy ears, wagging tail and all. Belyaev and Trut’s results have fundamentally changed how we think of the process of domestication: to enumerate all their findings and discuss their importance would require a book, which is why Lyudmila Trut (now 84 years old) and I wrote How to Tame a Fox (and Build a Dog)

Setting priorities: a new SPIHT-compatible algorithm for image compression

We introduce a new algorithm for progressive or multiresolution image compression. The algorithm improves on the Set Partitioning in Hierarchical Trees (SPIHT) algorithm by replacing the SPIHT encoder. The new encoder optimizes the multiresolution code performance relative to a user- defined probability distribution over the code's rates or resolutions. The new algorithm's decoder is identical to the SPIHT decoder. The resulting code achieves the optimal expected performance across resolutions subject to the constraints imposed by the use of the SPIHT decoder and the distribution over resolutions set by the user. The encoder optimization yields performance improvements at the rates or resolutions of greatest importance at the expense of performance degradation at low priority rates or resolutions. The algorithm is fully compatible at the decoder with the original SPIHT algorithm. In particular, the decoder requires no knowledge of the priority function employed at the encoder. Experimental results on an image containing both text and photographic material yield up to 0.86 dB performance improvement over SPIHT at the resolution of highest priority

Empathy in Nonhumans: A Brief Overview

We present a brief overview of the study of empathy in nonhumans.  We begin with a historical perspective that focuses on early ideas about empathy developed by Peter Kropotkin and Adam Smith. From there we discuss the origin and evolution of the multiple layers of empathy—emotional contagion,  sympathetic concern, and empathetic perspective-taking—casting that discussion within the “Russian doll model” of empathy developed by de Waal. For each layer we provide examples from the animal behavior literature

The geometrical pattern of the evolution of cooperation in the Spatial Prisoner's Dilemma: an intra-group model

The Prisoner's Dilemma (PD) deals with the cooperation/defection conflict between two agents. The agents are represented by a cell of $L \times L$ square lattice. The agents are initially randomly distributed according to a certain proportion $\rho_c(0)$ of cooperators. Each agent does not have memory of previous behaviors and plays the PD with eight nearest neighbors and then copies the behavior of who had the greatest payoff for next generation. This system shows that, when the conflict is established, cooperation among agents may emerge even for reasonably high defection temptation values. Contrary to previous studies, which treat mean inter-group interaction, here a model where the agents are not allowed to self-interact, representing intra-group interaction, is proposed. This leads to short time and asymptotic behaviors similar to the one found when self-interaction is considered. Nevertheless, the intermediate behavior is different, with no possible data collapse since oscillations are present. Also, the fluctuations are much smaller in the intra-group model. The geometrical configurations of cooperative clusters are distinct and explain the $\rho_c(t)$ differences between inter and intra-group models. The boundary conditions do not affect the results.Comment: 4 pages, 4 figure

Synchronization in Complex Systems Following the Decision Based Queuing Process: The Rhythmic Applause as a Test Case

Living communities can be considered as complex systems, thus a fertile ground for studies related to their statistics and dynamics. In this study we revisit the case of the rhythmic applause by utilizing the model proposed by V\'azquez et al. [A. V\'azquez et al., Phys. Rev. E 73, 036127 (2006)] augmented with two contradicted {\it driving forces}, namely: {\it Individuality} and {\it Companionship}. To that extend, after performing computer simulations with a large number of oscillators we propose an explanation on the following open questions (a) why synchronization occurs suddenly, and b) why synchronization is observed when the clapping period ($T_c$) is $1.5 \cdot T_s < T_c < 2.0 \cdot T_s$ ($T_s$ is the mean self period of the spectators) and is lost after a time. Moreover, based on the model, a weak preferential attachment principle is proposed which can produce complex networks obeying power law in the distribution of number edges per node with exponent greater than 3.Comment: 16 pages, 5 figure

Overestimating Resource Value and Its Effects on Fighting Decisions

Much work in behavioral ecology has shown that animals fight over resources such as food, and that they make strategic decisions about when to engage in such fights. Here, we examine the evolution of one, heretofore unexamined, component of that strategic decision about whether to fight for a resource. We present the results of a computer simulation that examined the evolution of over- or underestimating the value of a resource (food) as a function of an individual's current hunger level. In our model, animals fought for food when they perceived their current food level to be below the mean for the environment. We considered seven strategies for estimating food value: 1) always underestimate food value, 2) always overestimate food value, 3) never over- or underestimate food value, 4) overestimate food value when hungry, 5) underestimate food value when hungry, 6) overestimate food value when relatively satiated, and 7) underestimate food value when relatively satiated. We first competed all seven strategies against each other when they began at approximately equal frequencies. In such a competition, two strategies–“always overestimate food value,” and “overestimate food value when hungry”–were very successful. We next competed each of these strategies against the default strategy of “never over- or underestimate,” when the default strategy was set at 99% of the population. Again, the strategies of “always overestimate food value” and “overestimate food value when hungry” fared well. Our results suggest that overestimating food value when deciding whether to fight should be favored by natural selection

Prisoner's Dilemma cellular automata revisited: evolution of cooperation under environmental pressure

We propose an extension of the evolutionary Prisoner's Dilemma cellular automata, introduced by Nowak and May \cite{nm92}, in which the pressure of the environment is taken into account. This is implemented by requiring that individuals need to collect a minimum score $U_{min}$, representing indispensable resources (nutrients, energy, money, etc.) to prosper in this environment. So the agents, instead of evolving just by adopting the behaviour of the most successful neighbour (who got $U^{msn}$), also take into account if $U^{msn}$ is above or below the threshold $U_{min}$. If $U^{msn}<U_{min}$ an individual has a probability of adopting the opposite behaviour from the one used by its most successful neighbour. This modification allows the evolution of cooperation for payoffs for which defection was the rule (as it happens, for example, when the sucker's payoff is much worse than the punishment for mutual defection). We also analyse a more sophisticated version of this model in which the selective rule is supplemented with a "win-stay, lose-shift" criterion. The cluster structure is analyzed and, for this more complex version we found power-law scaling for a restricted region in the parameter space.Comment: 15 pages, 8 figures; added figures and revised tex