What Is It Like To Become a Bat? Heterogeneities in an Age of Extinction

In his celebrated 1974 essay “What Is It Like to Be a Bat?,” Thomas Nagel stages a human-bat encounter to illustrate and support his claim that “subjective experience” is irreducible to “objective fact”: because Nagel cannot experience the world as a bat does, he will never know what it is like to be one. In Nagel’s account, heterogeneity is figured negatively—as a failure or lack of resemblance—and functions to constrain his knowledge of bats. Today, as white-nose syndrome threatens bat populations across North America, might figuring heterogeneity positively, as a condition of creativity, open up new modes of receptivity and responsiveness to species extinctions? This essay turns to philosophies of becoming and to recent research in the biological sciences to explore this possibility. I suggest that attending to the heterogeneity of experience alerts us to more public dimensions of our being and may thereby work against the tendency to understand and experience ourselves as self-contained and closed off from one another and the world we share in common. This may in turn enhance our sense of entanglement with the events, bodies, and forces on the “outside” of experience, including bats and the white-nose syndrome with which they are afflicted today. Such an affirmation of heterogeneity as a condition of creativity holds the greatest promise for multispecies ethics today, I propose, when it is joined to an affirmation of incompatibilities within and between things as a real force of suffering and destruction in a heterogeneous world

From naive to sophisticated behavior in multiagents based financial market models

We discuss the behavior of two magnitudes, physical complexity and mutual information function of the outcome of a model of heterogeneous, inductive rational agents inspired in the El Farol Bar problem and the Minority Game. The first is a measure rooted in Kolmogorov-Chaitin theory and the second one a measure related with information entropy of Shannon. We make extensive computer simulations, as result of which, we propose an ansatz for physical complexity and establish the dependence of exponent of that ansatz from the parameters of the model. We discuss the accuracy of our results and the relationship with the behavior of mutual information function as a measure of time correlations of agents choice.Comment: 16 pages, 4 figures, submitted to Physica

UNDER-DIVERSIFICATION AND THE ROLE OF BEST REPLY TO PATTERN

Three experiments are presented that compare alternative explanations to the coexistence of risk aversion and under-diversification in investment decisions. The participants were asked to select one of several assets under two feedback conditions. In each case, one asset was a weighted combination of the other assets, allowing for lower volatility. The frequency of choice of the composite asset was highly sensitive to feedback condition. The composite asset was the least popular asset when the feedback included information concerning forgone payoffs, and increased in frequency when the feedback was limited to the obtained payoff. These results support the assertion that under-diversification can be a product of learning from feedback and in particular best reply to pattern.Risk; Diversification; Learning

On Surprise, Change, and the Effect of Recent Outcomes

The leading models of human and animal learning rest on the assumption that individuals tend to select the alternatives that led to the best recent outcomes. The current research highlights three boundaries of this “recency” assumption. Analysis of the stock market and simple laboratory experiments suggests that positively surprising obtained payoffs, and negatively surprising forgone payoffs reduce the rate of repeating the previous choice. In addition, all previous trails outcomes, except the latest outcome (most recent), have similar effect on future choices. We show that these results, and other robust properties of decisions from experience, can be captured with a simple addition to the leading models: the assumption that surprise triggers change

Introducing disappointment dynamics and comparing behaviors in evolutionary games : Some simulation results

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedThe paper presents an evolutionary model, based on the assumption that agents may revise their current strategies if they previously failed to attain the maximum level of potential payoffs. We offer three versions of this reflexive mechanism, each one of which describes a distinct type: spontaneous agents, rigid players, and 'satisficers'. We use simulations to examine the performance of these types. Agents who change their strategies relatively easily tend to perform better in coordination games, but antagonistic games generally lead to more favorable outcomes if the individuals only change their strategies when disappointment from previous rounds surpasses some predefined threshold.Peer reviewedFinal Published versio

Exact solution of a modified El Farol's bar problem: Efficiency and the role of market impact

We discuss a model of heterogeneous, inductive rational agents inspired by the El Farol Bar problem and the Minority Game. As in markets, agents interact through a collective aggregate variable -- which plays a role similar to price -- whose value is fixed by all of them. Agents follow a simple reinforcement-learning dynamics where the reinforcement, for each of their available strategies, is related to the payoff delivered by that strategy. We derive the exact solution of the model in the ``thermodynamic'' limit of infinitely many agents using tools of statistical physics of disordered systems. Our results show that the impact of agents on the market price plays a key role: even though price has a weak dependence on the behavior of each individual agent, the collective behavior crucially depends on whether agents account for such dependence or not. Remarkably, if the adaptive behavior of agents accounts even ``infinitesimally'' for this dependence they can, in a whole range of parameters, reduce global fluctuations by a finite amount. Both global efficiency and individual utility improve with respect to a ``price taker'' behavior if agents account for their market impact.Comment: 38 pages + 5 figures (needs elsart.sty). New results adde

Feeling the Vibrations: On the Micropolitics of Climate Change

Climate change is more than a discrete issue demanding political attention and response. A changing climate permeates political life as material processes of planetary change reverberate in our bodies, affecting subterranean processes of attention and evoking bodily responses at and below the register of awareness. By way of example, I explore the register of bodily feeling to raise the possibility that proliferating anomalies in atmospheric, oceanic, and seismic activities are entering into subliminal experiences of time and confounding embodied expectations of how the future is likely to flow from the past. The essay concludes with a preliminary discussion of how micropolitical strategies to amplify visceral experiences of climatic changes might valuably contribute to larger programs for climate action

Self-tuning experience weighted attraction learning in games

Self-tuning experience weighted attraction (EWA) is a one-parameter theory of learning in games. It addresses a criticism that an earlier model (EWA) has too many parameters, by fixing some parameters at plausible values and replacing others with functions of experience so that they no longer need to be estimated. Consequently, it is econometrically simpler than the popular weighted fictitious play and reinforcement learning models. The functions of experience which replace free parameters “self-tune” over time, adjusting in a way that selects a sensible learning rule to capture subjects’ choice dynamics. For instance, the self-tuning EWA model can turn from a weighted fictitious play into an averaging reinforcement learning as subjects equilibrate and learn to ignore inferior foregone payoffs. The theory was tested on seven different games, and compared to the earlier parametric EWA model and a one-parameter stochastic equilibrium theory (QRE). Self-tuning EWA does as well as EWA in predicting behavior in new games, even though it has fewer parameters, and fits reliably better than the QRE equilibrium benchmark