Thesis research at the University of Minnesota (19745) on Games, Goals, and Bounded Rationality.

Leigh Tesfatsion, "Two Essays on Individual Choice"
(pdf,2.5MB),
PhD Thesis, Department of Economics, 7615,007 University of Minnesota, Mpls., December 1975.

The key idea of this thesis is that boundedlyrational decisionmakers can supplement partial contingency plans with goals,
thus permitting actions to be undertaken in desired directions despite the absence of complete information. An expected utility model permitting goaldirected action choice is formulated and axiomatized for concrete demonstration.
Work at the University of Minnesota (19745) and University of Southern California (19751984) on
Criterion Filtering.

The following question arises for sequential decisionmaking under uncertainty: Can the associative mapping between decisions and expected payoffs be directly updated, without recourse to the updating of probabilities?

Criterion Filtering (CF) provides an affirmative answer to this question. CF is a learning algorithm that permits the direct updating of expected utility on the basis of sequentially realized utility outcomes, conditional on prior (initial) utility assessments. The CF algorithm thus provides a "Bayes' Rule for Utility".


Criterion Filtering (CF): A Dual Approach
to Bayesian Inference and Adaptive Control
Work at University of Southern California (19751990) with applied mathematician Bob Kalaba on Flexible Least Squares.
 Flexible Least Squares (FLS) is a multicriteria optimization method for model specification. The goal of the FLS method is to identify the "Pareto frontier" of all efficiently estimated models conditional on: (i) a given theory; (ii) a given data set; and (iii) a designated collection of goodnessoffit metrics. FLS does not require the imposition of problematic stochastic assumptions on "residual error terms" that in fact arise from deterministic model misspecification.

Flexible Least Squares (FLS): A Multicriteria Optimization Method for Model Specification
Work at USC (19751990) with applied mathematician Bob Kalaba on Adaptive Computation.

An adaptive computation method adapts to the problem at hand rather than requiring the problem to be adapted to the method.
Bob Kalaba and I developed adaptive computation methods for the solution of various types of nonlinear problems.

For example, we developed an adaptive homotopy solution algorithm able, in runtime, to detect and avoid regions where calculations are illconditioned due to nearby singularities or bifurcation points. This adaptive capability is achieved by replacing the standard homotopy continuation parameter, moving in a preset manner from 0 to 1 along the real line, with a "smart agent" able to construct and traverse an adaptively determined path from 0+0i to 1+0i in the complex plane. The smart agent decides the direction and length of its next step, given its current state, by solving a multicriteria optimization problem requiring a tradeoff between two criteria: (i) maintain a short path length from 0+0i to 1+0i; and (ii) avoid regions in the complex plane where illconditioning of calculations is detected.

Adaptive Computation Methods for Nonlinear Systems;
Work at USC (19751990) and ISU (1990present) on
Modeling of Economies as OpenEnded Dynamic Systems.
 This work includes, for example, the modeling of macroeconomies as DSGL systems, where
DSGL = DSG(~E) + Learning Agents.

More precisely, DSGL systems are Dynamic,
Stochastic, and General marketbased macroeconomic systems for which decisionmaking agents have Learning capabilities. Coordination arises endogenously (if at all) in DSGL systems as a result of successive agent interactions, not from the external imposition of equilibrium assumptions.

Optimality and Efficiency of
OpenEnded Dynamic Economies
Work at ISU (19902001) on the Blending of Game Theory with Matching Theory.

Trading games are explored for concrete demonstration. The endogenous preferential choice and refusal of trading partners (matching theory) is modeled, together with the evolution of trading strategies (game theory). At each point in time the selection of trading partners, and the selection of trading strategies for use with these partners, are determined on the basis of past trade outcomes and initially held beliefs.

The Trade Network Game (TNG) Laboratory is opensource demonstration software permitting the beautiful runtime visualization of endogenous tradenetwork formation among strategic buyers, sellers, and dealers in a sequential trade network game.

Endogenous Trade Network Formation
and the TNG Laboratory;
Work at ISU (1990present) on
completely AgentBased Modeling (cABM) and
Agentbased Computational Economics (ACE).

Scientists and engineers seek to understand how realworld systems work, and how realworld systems could work better. Any modeling approach devised for such purposes must simplify reality. Ideally, however, the modeling approach should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand.

Modeling flexibility and logical rigor have been the two key goals motivating my development of completely AgentBased Modeling (cABM)
and Agentbased Computational Economics (ACE). The
cABM modeling approach is a variant of agentbased modeling characterized by seven modeling principles. Any model adhering to these seven modeling principles is a computational laboratory permitting explorations of computational systems in a manner analogous to biological experimentation with cultures in Petri dishes. The ACE modeling approach is a specialization of cABM to economic systems.

Completely AgentBased Modeling (cABM)

AgentBased Computational
Economics (ACE): Homepage
Work at ISU (2011present) on a Linked SwingContract Market Design for Wholesale Electric Power Markets

Good market design begins with an appropriate conceptualization of the product being transacted. For centrallymanaged wholesale electric power markets operating over highvoltage transmission grids, this product is physicallycovered insurance ("reserve") permitting central managers to protect against volumetric risk. This volumetric risk is possible imbalance between the "justintime" power demands of diverse customers at various grid locations and the availability of "justintime" dispatchable power supplies.

In the Wiley/IEEE Press book cited below, a linked swingcontract market design is proposed for centrallymanaged wholesale power markets to facilitate increased reliance on renewable power together with more active demandside participation. The proposed swing contracts are twopart pricing contracts, in firm or option form, that permit dispatchable power resources to offer reserve (i.e., dependable availability of diverse powerbalancing capabilities) for designated future operating periods in return for appropriate compensation. These swing contracts are submitted into a collection of linked forward markets M(OP) managed by a system operator for successive future operating periods OP. The system operator determines an optimal contractclearing solution for each market M(OP) to protect against volumetric risk during OP.

Leigh Tesfatsion (2021), A New SwingContract Design for Wholesale Power Markets, 20 Chapters, 288pp., John Wiley & Sons, Inc. (IEEE Press Series on Power Engineering), Hoboken, New Jersey, USA.
(Book Review,pdf),
(Presentation,SlideSet,pdf),
(Wiley/IEEE Press Book Flyer,pdf).
Work with electric power engineers at ISU (2000present) on marketbased designs for Integrated Transmission and Distribution Systems.

The growing reliance of centrallymanaged wholesale electric power markets on renewable power resources poses new challenges for these markets. For example, intermittent resources such as wind power and solar power that are not backstopped by storage can make it more difficult to balance power withdrawal (usage & losses) with power injection (supply) across a transmission grid, a prerequisite for reliable grid operations.

These challenges have led to efforts by the U.S. Federal Energy Regulatory Commission  such as FERC Order 2222 (Final Rule) released in September 2020  to increase the participation of distributed power resources in these markets in dispatchable aggregated form. Transactive Energy System (TES) design is a relatively new approach to electric power management that could provide important support for FERC Order 2222 objectives.

In response to these trends, our ISU project on
Integrated Transmission and Distribution (ITD) systems has developed
various types of TES designs to facilitate the efficient reliable provision of power and ancillary services from a wide array of ITD power resources in return for appropriate compensation. This ITD TES design research has been supported by the development of agentbased computational platforms representing the salient operations of actual electric power systems.

Integrated Transmission and Distribution (ITD)
Project: ISU Homepage