Evolutionary, Cognitive Neuro-Psychology

Computer stuff is below

Over the last few years I have rekindled my first love — neurobiology — to explore the nature of real intelligence. This follows naturally from my work on autonomous agents (below) but has led me into a rather interesting realm that would not be obvious to those who have come to cognitive science strictly from the field of artificial intelligence.

The advances in understanding how the brain works have literally exploded over the last several decades, and particularly in the first decade of the 21^st century. Many disciplines are converging on the workings of the human mind. From psychology we continue to refine probes of behavior and decision making/problem solving. From neurobiology, especially with the advent of dynamic imaging techniques, we have begun to map control functions to specific areas of the brain. And from Evo-Devo (evolution and development taken together) we are beginning to understand how the modern human brain came into existence and how it helped Homo sapiens emerge as the dominant hominid as well as a symbol manipulating (language and signs) sentience. These are extraordinarily exciting times in brain research.

But a major puzzle has developed as we understand intelligence, creativity, and affect (emotions and feelings) in their evolutionary and contemporary contexts. Humans, even the most intelligent ones, often fail to make good judgments. Age helps, but is no guarantee that people will make wise choices. Many psychologists have begun to explore the psychological basis of wisdom and have defined a recognizable construct which they can probe with tests similar to those used to probe intelligences. It is now reasonably clear that wisdom is related to intelligence, but is not just more intelligence. It involves reflective judgment and a wealth of tacit life-knowledge. Wise people make choices of what to turn their intelligence and creativity to, of what to learn and what knowledge is useful in solving complex life and social problems. Wisdom involves superior moral judgments that benefit the largest numbers for the longest times.

At the same time neurobiologists are determining the capabilities of the prefrontal cortex in its role of providing so-called executive functions in guiding the reasoning and problem solving abilities of the mind. Recently attention has turned to the prefrontal cortex, particularly the extreme pole patch of tissue (right behind the eyes!) in processing judgment. My interest is in determining if this processing, which I have labeled sapience in order to distinguish the cognitive aspect from the performance and knowledge-base aspects of wisdom, is, indeed, the basis of what we recognize as wisdom.

A major question, from an evolutionary perspective, is this: If the human brain has evolved a higher form of judgment, geared presumably to the life problems faced by late Pleistocene hominids, is that capability sufficient to guide us in our present circumstances? This is a sociological question as much as an evolutionary or psychological one. Is modern Homo sapiens wise enough to make good choices on global and multi-generational scales?

Recent political events across the world, overpopulation and over-consumption of non-renewable resources, which seem to reflect that we, as a species, have not learned much from history, would suggest that the answer to that question is no.

In addition to the working papers available below I write extensively about sapience and many of the global challenges that are testing our collective capacity for wisdom in my personal blog Question Everything. The motivation for this blog came from my experiences teaching the Global Honors course, Global Challenges in which I have attempted to apply systems science to the analysis of the problems and construction of solutions.

Working Papers on Sapience

1. Sapience Introduction

2. Sapience - Relationship with Cleverness and Affect

3. The Components of Sapience Explained

4. The Neuroscience of Sapience

5. The Evolution of Sapience, Past and Future (Still in development)
See this Power Point presentation given at the Science, Wisdom, and the Future conference.

Here is a partial bibliography of books that I have found particularly interesting in this quest.

And here is a bibliography of books on global issues that support the suggestion that we humans are not very wise as a species.

Biophysical Economics

For a long time I have had an interest in the relationship between energy and economics, namely the fact that energy is the real currency of economic activity. This interest has been largely informal but I have kept abreast of the ideas that have been developing in the field of Ecological Economics, which is related. In the last few years the role of energy flow in the economy, and in particular with respect to the production of real wealth (as opposed to paper assets), has increasingly been seen as central to the global economy.

Last fall I stepped into a more formal approach with the presentation of a talk at the first meeting of the Biophysical Economics Society (actual name yet to be determined!) at SUNY-ESF in which I argued that the monetary system should be tied directly to the amount of exergy, or energy available to do useful work (e.g. electricity or refined gasoline) potential. The idea of basing money on energy is not new, but my contribution is to provide a more readily determinable definition of money/energy that can be used for measuring economic activity and wealth.

This fall I will be taking my sabbatical at SUNY-ESF to further develop my interests in this field. Professor Charlie Hall is widely known as the leading expert on energy return on energy invested (EROI) analysis. I hope to learn more about his methods and data sources as well as work on a model of economic activity that combines the effects of EROI with the peaking of oil production that appears to have recently passed. Peak oil may be one of the more paradigm-shifting forces affecting our current models of economics. My own suspicion is that the combined effects of peak oil and diminishing EROI are the real factors underlying the current economic crisis. See my blog writings on the subject for more background.

Computational Projects

My interest in the above research area, especially in light of the various global issues that face humanity, has motivated me to apply my computer science background to projects that just might contribute to the analysis and solving of some of these problems.

I have started two projects that are directed at producing tools for analyzing complex systems problems, both technical and social. One project involves the development of a new systems dynamics modeling language to aid researchers in studying highly complex, hierarchically structured dynamic systems. The other project involves developing a global-scale, structured, e-discourse platform that will allow participants from all over the globe to help in the top-down analysis and bottom-up design of solutions to complex social and policy problems (so-called "wicked" problems).

DynSysMod is a new modeling language for expressing discrete time models of a wide variety of concrete systems. If you are familiar with languages such as DYNAMO or STELLA you may appreciate the benefits that DynSysMod should provide. For starters we have explicitly identified three different types of flows — matter, energy, and messages. This makes it easier to create models of systems that have large inputs of free energy to drive production processes. After several years of trying to delineate these separate flows in STELLA and ending up with incredibly complex models that were difficult to interpret it became apparent that real systems would be better represented if the flows were segregated.

Another innovation planed for DynSysMod is to provide a method for representing models in hierarchical decomposition or upward composition. In other words one can start defining a model from a very high level macro-view and then decompose the system into its component subsystems. Alternatively one can define a system that can later be combined with another system operating in the same time domain. In part this will be achieved by allowing different levels in the hierarchy to operate with different time step increments. For example a shop floor might be updated on an hourly basis while the inventories could be updated on a daily basis. We are currently exploring the computational efficiencies that might be gained by taking this approach as opposed to updating an entire model by just the smallest time increment of any of its components.

DynSysMod is being developed primarily to allow those interested in energy systems to test various aspects of, say, an alternative energy system such as solar photovoltaics or wind. I began this project in response to the difficulties I encountered in modelling what I call the Energy Systems Sustainability Criterion. This criterion is relatively simple to understand but fiendishly difficult to get ahold of in practice. It says that any energy conversion capital equipment (such as solar panels or wind turbines) must, in the long run, produce enough excess energy above that consumed in the economy, to maintain and replace itself when its useful life is over. At first glance this might seem like a simple thing to verify, but it has second and higher order aspects, such as there must be enough energy to account for the fraction of energy used to maintain and build the manufacturing plant where the capital equipment is produced (as well as cover other work-costs). A modelling language that breaks out the explicit flows and reservoirs of energy, as well as captures the first and second laws of thermodynamics, should be very helpful in determining how energy flows through such a complex macro-system.

See MS graduate Jennifer Leaf's final project report covering the first phase of this project.

Electronic Discourse Systems: The ConsensUs Project

I have recently embarked on developing a new e-discourse system code-named "ConsensUs", which extends concepts of structured discourse for problem exploration and solving. This system will employ latent semantic analysis (think of Google's "Similar pages" feature) to aggregate and consolidate large volumes of commentary as a means of assisting moderators and managing information overload.

The purpose of ConsensUs is to support global-scale discourse for global-scale problems like global warming/climate change. Current e-discourse systems do not seem to scale well. We hypothesize that the form of structure used and the use of semantic analysis, and other techniques, will allow ConsensUs to scale well. Additionally, while the alpha development system is being built on Web technologies, we plan to port the system to a peer-to-peer (P2P) platform such as Sun Microsystem's JXTA project.

The ConsensUs Web site gives an (as yet incomplete) description of the project. This project is being developed by my students under the direction of myself and Don McLane. Both undergraduate and graduate students are participating in developing the initial code base. We plan to open this project up for open-source development once that base is in place. Stay tuned for further developments!

Adaptive, Autonomous, Artificial Agents/Architecture

See the Adaptive Agents Lab Web Site

Foraging search -- inspired by how animals find food -- relies on a causal relation heuristic.  It assumes that there are, associated with each sought resource object, a group of objects which have a causal relationship with the sought resource object.  Such objects are called "cues". In the absence of a cue (labelling a path out of a given node) a stochastic component selects a path randomly on each iteration of a depth-first-search.  If, however, a cue is detected, the agent switches to a directed search (best-first-search). The trick is in how the agent is to learn what constitutes valid cues.  I have been investigating the learning competence of the Adaptrode mechanism along with the architecture necessary to learn and use causal relations for guiding search. 

I have extended the concept of foraging search into the realm of prototypical intelligence.  That is, the brain mechanisms needed to conduct foraging search behavior can be used to explain mental processes that we call thinking.  What interest me is the progression from reactive systems, through adaptive and anticipative systems, to intelligence.  Is it possible that anticipative behavior is the basic, possibly only, necessary one for the evolution of intelligence in animals?