Modelling exploration and exploitation in organizational learning

Abstract. Simulations have been utilized in organizational learning research since the early 1960s. Despite organizational and management sciences being early adopters of the simulation-based research and theory construction and while other disciplines have begun to adopt simulations as part of their research the simulation-based research never reached its expected popularity in organizational- and management sciences despite its promising beginnings. The purpose of this bachelor’s thesis is to create a holistic view of simulation modelling in organizational and management sciences which will function as a basis for one of the most fundamental models in organizational knowledge research. In this work we will explore how the March (1991) simulation model and the article has evolved over the last three decades. By exploring the model this work will also create a comprehensive view about the development of organizational learning and the related concepts in the field as well as showcase the significance of simulation modelling as part of organizational learning development. At the center of this thesis however is the argument represented by the March (1991) simulation model about the fundamental competition for scarce resources between organizational exploration and exploitation and their impact in organization’s knowledge and performance rates. In this thesis we will create a comprehensive view of the supposed dilemma between exploration exploitation in organizational learning and offer suitable solutions for this problem based on simulation modelling and empirical research. As a part of this thesis I will construct a conceptual model that will function as a basis for a future reconstruction of the original March (1991) simulation model. The purpose of the reconstruction is to validate the original model as well as make the model more communicable, visualizable and updateable. The work will serve as an excellent basis for future extensions in to the model and offers a strong basis for future research into modelling in organizational- and management sciences.Tiivistelmä. Simulaatioita on hyödynnetty organisaatio oppimiseen liittyvässä tutkimuksessa 1960-luvulta saakka. Vaikka organisaatio- ja johtamistieteet olivat hyvin aikaisia simulaatiopohjaisen tutkimuksen ja teorian rakentamisen edelläkävijöitä ja samalla kun myös monet muut tieteenalat ovat alkaneet omaksumaan simulaatioiden hyödyntämisen tutkimuksessa eivät simulaatiot koskaan saavuttaneet oletettua suosiota organisaatio- ja johtamistieteissä lupaavasta alusta huolimatta. Tämän kandidaatintyön tarkoituksena on luoda kokonaisvaltainen kuva simulaatio- ja mallintamiskäytännöistä organisaatio- ja johtamistieteissä, joka toimii pohjana työssä tarkasteltavalle organisaatio oppimisen keskeisimmän mallin tarkastelulle ja sen kehitykselle viimeisen kolmen vuosikymmenen aikana. Mallin tarkastelun avulla luodaan myös kattava kuva organisaatioiden oppimiseen liittyvien ajatusten ja käsitteiden kehittymisestä sekä mikä rooli mallinnuksella on ollut osana organisaatio oppimisen kehitystä. Työn keskiössä on March (1991) esille nostama argumentti organisaatioiden resurssien kohdistamisesta olemassa olevan osaamisen ja teknologian hyödyntämisen (exploitation) ja uuteen teknologiaan ja osaamiseen liittyvän tutkimuksen (exploration) välillä. Työssä tarkastellaan organisaatioiden kykyä ja tarvetta tasapainotella edellä mainitun kahden resurssin välillä sekä niiden vaikutusta organisaatioiden osaamistasoon ja suorituskykyyn niin lyhyellä kuin pitkällä aikavälillä. Työssä luodaan laaja kokonaiskuva lyhyen- ja pitkän aikavälin hyödyn tavoittelun välisistä oletetuista ristiriidoista sekä tarjotaan mahdollisia ratkaisuja mallinnuksen ja empiirisen tutkimuksen pohjalta. Osana työtä rakennan konseptuaalisen mallin tarkastellun March (1991) mallin ja työssä tarkasteltujen töiden pohjalta, jonka tarkoituksena on toimia pohjana toteutettavalle mallin rekonstruktiolle. Mallin rekonstruktion tehtävänä on toimia validointina alkuperäiselle mallille sekä tehdä mallista helpommin kommunikoitava, visualisoitava ja uudelleenpäivitettävä. Työ tarjoaa erinomaisen pohjan mallin jatkokehitykselle ja mallinnukseen liittyvälle jatkotutkimukselle organisaatio- ja johtamistieteissä

An exploration and validation of computer modeling of evolution, natural selection, and evolutionary biology with cellular automata for secondary students.

The Evolutionary Tool Kit, a new software package, is the prototype of a concept simulator providing an environment for students to create microworlds of populations of artificial organisms. Its function is to model processes, concepts and arguments in natural selection and evolutionary biology, using either Mendelian asexual or sexual reproduction, or counterfactual systems such as \u27paint pot\u27 or blending inheritance. In this environment students can explore a conceptual What if? in evolutionary biology, test misconceptions and deepen understanding of inheritance and changes in populations. Populations can be defined either with typological, or with populational thinking, to inquire into the role and necessity of variation in natural selection. The approach is generative not tutorial. The interface is highly graphic with twenty traits set as icons that are moved onto the \u27phenotypes\u27. Activities include investigations of evolutionary theory of aging, reproductive advantage, sexual selection and mimicry. Design of the activities incorporates Howard Gardner\u27s Theory of Multiple Intelligences. Draft of a teacher and student manual are included

Structural Drift: The Population Dynamics of Sequential Learning

We introduce a theory of sequential causal inference in which learners in a chain estimate a structural model from their upstream teacher and then pass samples from the model to their downstream student. It extends the population dynamics of genetic drift, recasting Kimura's selectively neutral theory as a special case of a generalized drift process using structured populations with memory. We examine the diffusion and fixation properties of several drift processes and propose applications to learning, inference, and evolution. We also demonstrate how the organization of drift process space controls fidelity, facilitates innovations, and leads to information loss in sequential learning with and without memory.Comment: 15 pages, 9 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/sdrift.ht

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field