Christoph Adami

Last updated 7.26.2010

Selected Publications

Iliopoulos, D.; Hintze, A.; Adami, C. "The evolution of cooperation by natural selection" arxiv.org arXiv:1004.2020v1, PLoS Comp. Biol. (in review)

Østman, B.; Hintze, A.; Adami, C. "Impact of epistasis and pleiotropy on evolutionary adaptation" arxiv.org arXiv:0909.3506v1 (in review)

Hintze, A.; Adami, C. "Modularity and anti-modularity in networks with arbitrary degree distribution" Biology Direct 5 (2010)

Marstaller, L.; Hintze, A.; Adami, C. "Measuring representation" in W. Christensen, E. Schier & J. Sutton (Eds), ASCS09: Proceedings of the 9th Conference of the Australasian Society for Cognitive Science (2010)

Adami, C. "Biological complexity and biochemical information" Encyclopedia of Complexity and Systems Science , R. Meyers, ed., Springer Verlag (2009)

Iliopoulos, D.; Szor, P.; Adami, C. "Darwin inside the machines: Malware evolution and the consequences for computer security" Virus Bulletin 2008: p.178 (2008)

Hintze, A.; Adami, C. "Evolution of complex modular biological networks" PLoS Comp. Biol.4, e23 (2008)

Chaumont, N.; Egli, R.; Adami, C. "Evolving virtual creatures and catapults" Artificial Life13: 139-157 (2007)

Adami, C. "Who watches the watcher?" Science 316:1125-1126 (2007)

Adami, C. "What do robots dream of?" Science 314: 1093-1094 (2006)

Adami, C. "Digital genetics: unraveling the genetic basis of evolution" Nature Reviews Genetics 7: 109-118 (2006)

Adami, C. "Reducible Complexity" Science 312: 61 - 63 (2006)

Forster, R.; Adami, C.; Wilke, C.O. "Selection for mutational robustness in finite populations" J. theor. Biology 243:181-190 (2006)

Drummond, D.A.; Bloom, J.D.; Adami, C.; Wilke, C.O.; Arnold, F.H. "Why highly expressed proteins evolve slowly" Proc. Natl. Acad. Sci. U.S.A. 102: 14338-14343 (2005)

Bloom, J.D.; Silberg, J.J.; Wilke, C.O.; Drummond, D.A.; Adami, C.; Arnold, F.H. "Thermodynamic prediction of protein neutrality" Proc. Natl. Acad. Sci. U.S.A. 102: 606-611 (2005)

Adami, C.; Wilke, C.O. "Experiments in digital evolution" (Editors' Introduction), Artif. Life10: 117-122 (2004)

White, J.S.; Adami, C. "Bifurcation into functional niches in adaptation" Artif. Life 10: 135-144 (2004)

Edlund, J.A; Adami, C. "Evolution of robustness in digital organisms" Artif. Life 10: 167-179 (2004)

Hampton, A.N.; Adami, C. "Evolution of robust developmental neural networks" Proc. Artificial Life IX, Boston, MA, Sep 12-15, (2004) Pollack, J.; Bedau, M.A.; Husbands, P.; Ikegami, T.; Watson, R. eds., MIT Press p 438-443 92004)

Wagenaar D.A.; C. Adami, C. "Influence of chance, history, and adaptation on digital evolution" Artif. Life 10: 181-190 (2004)

Campos, P.R.A.; Wilke, C.O; Adami, C."Modeling stochastic clonal interference" in Modelling in Molecular Biology (Springer Series in Natural Computing) Ciobanu, G.; Rozenberg, G. eds. pp. 21-39 (2004)

Bloom, J.D.; Wilke, C.O.; Arnold, F.H.; Adami, C."Stability and evolvability of function in a model protein" Biophys. J.86: 2759-2764 (2004)

Adami, C. "Information theory in molecular biology" Physics of Life Reviews 1: 3-22 (2004)

Chow, S.S.; Wilke, C.O.; Lenski, R.E.; Ofria, C.; Adami, C."Adaptive radiation from resource competition in digital organisms" Science 305: 83-85 (2004)

7.26.2010

Evolution of Artificial Brains for Autonomous Robots

We are exploring an approach to evolutionary robotics where the control structures ("artificial brains") are hierarchical stochastic logic networks that we evolve to function in complex and dynamic environments. The networks are encoded genetically and learn to predict the world in which the robots function. By bridging the timescales between synaptic and genetic (Darwinian) learning, we are attempting to create intelligently behaving mobile systems. In the first stage, both robots and control structures are simulated in the computer, but a transition to hardware is expected in the second phase.

Synergistic Information Processing in Neuronal Networks

One of the hallmarks of intelligent information processing is the capacity to integrate information from different sensory modalities in such a manner that the whole (our impression of an object or a dynamical scene) is more than the sum of its parts. A framework to describe integrated information processing within the theory of information (Integrated Information Theory, or IIT) has recently been developed (Balduzzi & Tononi 2008), and we are exploring both the structure of that theory and its application to evolving artificial brains. One of the projects involves the development of heuristic search algorithms for a graph partitioning problem.

D. Balduzzi & G. Tononi (2008). Integrated information in discrete dynamical systems: Motivation and theoretical framework. PLoS Comp. Biol. 4:1000091.

Causes and Consequences of Speciation in Sympatry

There is much debate about whether speciation can occur in sympatry, and how prevalent this mode of speciation is. We are attempting to understand, via computational simulations, what the processes are that make speciation in sympatry possible, what traces the sympatric process leaves in the sequences of the species, and how these traces can be detected in the sequences of existing taxa. We are testing a theory that implies that sympatric speciation occurs mainly via ecological specialization, simultaneous with or followed by the emergence of assortative mating based on ecologically functional or neutral characters. We will study this hypothesis via computational simulations, map the "envelope" of parameters that lead to speciation in sympatry, and conduct control simulations that show speciation in allopatry or parapatry. We will analyze the patterns of the speciation process left behind in the sequences with network biology tools, to develop a signature that can distinguish between the processes. We will then test this signature on sequence data of existing taxa.

Stochastic Strategies in Evolutionary Games

Evolutionary Game Theory attempts to understand the emergence of cooperation in games in which defection (that is, the non-cooperative strategy) is the rational solution. Examples of such games are the Prisoner's Dilemma, the Snowdrift game, the Traveler's Dilemma, the Centipede Game, and the Ultimatum Game. Unlike the standard literature, we are exploring the evolution of stochastic strategies in a fully Darwinian setting where the decision probabilities are encoded genetically and adapt to respond optimally to their environment.

Evolution Experiments with Digital Organisms

Digital organisms are self-replicating computer programs that compete with each other and evolve and adapt to a user-specified environment. These organisms (a form of non-terrestrial life) have been used extensively to study fundamental problems in evolutionary biology, from the evolution of complex features, to the problem of speciation and the evolution of sex. Many other problems can be addressed with digitals. Among the most interesting are the evolution of sexual recombination and its relation to parasitism, the origin of genome complexity via genome doubling events, and the origin of information. The Adami lab is studying how information can be generated spontaneously in a transition from a thermodynamical regime of random sequences to an information-dominated regime.

Structure and Origin of Functional Modules in Cellular Biology

Biological function is the complex consequence of the action of a large number of molecules that interact in many different ways. Elucidating the contribution of each molecule to a particular function would seem hopeless, had evolution not shaped the interaction of molecules in such a way that they form functional units, or building blocks, of the organisms function. These building blocks can be called modules, whose interactions, interconnections, and fault-tolerance can be investigated from a higher-level point of view, allowing for a synthetic view of biological systems. We are taking an integrated computational and experimental approach to determine the extent of modularity in the gene-interaction network, the properties of modules, their contribution to robustness and fault-tolerance, their origin and evolution, and how existing and emerging criteria of module definition and function affect our ability to predict biological function.

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