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Handbook of Computational Economics: Agent-Based Computational Economics (Volume 2)
The explosive growth in computational power over the past several decades offers new tools and opportunities for economists. This handbook volume surveys recent research on Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic systems of interacting agents. Empirical referents for "agents" in ACE models can range from individuals or social groups with learning capabilities to physical world features with no cognitive function. Topics covered learning; empirical validation; network economics; social dynamics; financial markets; innovation and technological change; organizations; market design; automated markets and trading agents; political economy; social-ecological systems; computational laboratory development; and general methodological issues.
*Every volume contains contributions from leading researchers*Each Handbook presents an accurate, self-contained survey of a particular topic *The series provides comprehensive and accessible surveys
*Every volume contains contributions from leading researchers*Each Handbook presents an accurate, self-contained survey of a particular topic *The series provides comprehensive and accessible surveys
904 pages, Hardcover
First published July 14, 2006
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December 30, 2017
Vol. II of this truly remarkable compendium by L. Tesfatsion & K. Judd. In this one you will find a pretty wide gamut of extensive contributions to the most diverse agent-modelling techniques (worth mentioning at least the multiple nash equilibria solving methods, nonoptimal heuristics, dimensional reduction and also lots of good examples all along; a few of which struck me as quite bizarre, honestly).
I’m pretty glad it served well as a solid overture on how the enstablished state-of-the-art modeling methods have dealt with their objects as a broader approach over the last decades: population dynamics/ecology, social modeling and politics included.
Anyways, in a pretty unexpected twist–by which I mean as anyone could presciently guess, since it's not the focus of the book–I couldn’t help noticing how the authors either seem to consiliently fail at making a real case for ABM as a preferred slant and 'market-ing' their brand, or maybe they are uninterested to convey to what extent the added value of ABM would significantly change the games in town (except for task-specific, well-enstablished instances that are already used), and not be an ancillary/complementary simulation tale at best. This, apparently, comes with the intended plus of presenting the stuff more in the guise of an empirical assessment envisioned as a new, yet mature, line of inquiry with its own amount of results (rather than a wide-ranging methodological discourse; which is not lacking, nontheless) - and it's a fairly successful plus. I’m under the impression that while asking the wrong questions to this book, I kind of came across some few quibbles that, say, a ~serius scholar~ may happen to have with microfoundation/foundamentalism arguments underpinning some of these studies, above all when taken as granted or just randomly sketched out as unproblematic (without any serious attempt to justify WHY, HOW...). That would be, I guess, a cautious case for the missed link of the 'emergence' at macro scale from a microstate model, which seem to me basically resting upon the quite annoying assumption that the macro pattern of regularities might rely on the local level of agent's interactions... but how's that? Is it just another n-body problem? That is mostly concurrent–if not patently at odds–with the dimensional reduction methods (the ones that, in any case, spring into existence because of computability issues on the state-space of agents parameters), which implicitly suggest that there is a turning point at some aggregated scale beyond which agents simply _don’t matter_ anymore. I couldn't fathom howa AB-modeller intend to cope with this cumulative-scale effect without recognizing that maybe 'agents are not the point, after all?'... and, in fact, I found it a bit frustrating that there isn't a page in this book to seriusly address this conundrum. So, for what is worth, and it amounts to absolute nothing, I decided that I don't believe agents do matter at some macro scales (even way before that macro scale, if I must; I bet you're happy now, aren't you!?)
I’d rather be happy to miss something in this, and it certainly is the case. But, welp, be it as it may, it can be asserted that the handbook does not even try to provide hints of an answer on this point.
I’m pretty glad it served well as a solid overture on how the enstablished state-of-the-art modeling methods have dealt with their objects as a broader approach over the last decades: population dynamics/ecology, social modeling and politics included.
Anyways, in a pretty unexpected twist–by which I mean as anyone could presciently guess, since it's not the focus of the book–I couldn’t help noticing how the authors either seem to consiliently fail at making a real case for ABM as a preferred slant and 'market-ing' their brand, or maybe they are uninterested to convey to what extent the added value of ABM would significantly change the games in town (except for task-specific, well-enstablished instances that are already used), and not be an ancillary/complementary simulation tale at best. This, apparently, comes with the intended plus of presenting the stuff more in the guise of an empirical assessment envisioned as a new, yet mature, line of inquiry with its own amount of results (rather than a wide-ranging methodological discourse; which is not lacking, nontheless) - and it's a fairly successful plus. I’m under the impression that while asking the wrong questions to this book, I kind of came across some few quibbles that, say, a ~serius scholar~ may happen to have with microfoundation/foundamentalism arguments underpinning some of these studies, above all when taken as granted or just randomly sketched out as unproblematic (without any serious attempt to justify WHY, HOW...). That would be, I guess, a cautious case for the missed link of the 'emergence' at macro scale from a microstate model, which seem to me basically resting upon the quite annoying assumption that the macro pattern of regularities might rely on the local level of agent's interactions... but how's that? Is it just another n-body problem? That is mostly concurrent–if not patently at odds–with the dimensional reduction methods (the ones that, in any case, spring into existence because of computability issues on the state-space of agents parameters), which implicitly suggest that there is a turning point at some aggregated scale beyond which agents simply _don’t matter_ anymore. I couldn't fathom how
I’d rather be happy to miss something in this, and it certainly is the case. But, welp, be it as it may, it can be asserted that the handbook does not even try to provide hints of an answer on this point.
Displaying 1 of 1 review