Biomedical Engineering Reference
In-Depth Information
121. Moore C, Nordahl MG. 1997. Lattice gas prediction is P-complete. Electronic preprint
(http://arxiv.org/abs/nlin.CG/9704001).
122. Hardy J, Pomeau Y, de Pazzis O. 1976. Molecular dynamics of a classical lattice gas: transport
properties and time correlation functions.
Phys Rev A
13
:1949-1960,.
123. Frisch U, Hasslacher B, Pomeau Y. 1986. Lattice-gas automata for the Navier-Stokes equation.
Phys Rev Lett
56
:1505-1508.
124. Rothman DH, and Zaleski S. 1997.
Lattice-gas cellular automata: simple models of complex
hydrodynamics
. Cambridge UP, Cambridge.
125. Fisch R, Gravner J, Griffeath D. 1991. Threshold-range scaling of excitable cellular automata.
Stat Comput
1
:23-39 (http://psoup.math.wisc.edu/papers/tr.zip).
126. Nilsson M, Rasmussen S, Mayer B, Whitten D. 2003. Constructive molecular dynamics (MD)
lattice gases: 3-D molecular self-assembly. In
New constructions in cellular automata
, pp.
275-290. Ed. D Griffeath, C Moore. Oxford UP, Oxford.
127. Nilsson M, Rasmussen S. 2003. Cellular automata for simulating molecular self-assembly.
Discr Math Theor Comput Sci
AB(DMCS):31-42 (http://dmtcs.loria.fr/proceedings/html/
dmAB0103.abs.html).
128. Bartlett MS. 1955.
An introduction to stochastic processes, with special reference to methods
and applications
. Cambridge UP, Cambridge.
129. Jacquez JA, Koopman JS, Simon CP, Longini IM. 1994. The role of the primary infection in
epidemics of HIV-infection in gay cohorts.
J Acq Immune Def Synd Hum Retrovirol
7
:1169-
1184.
130. Koopman J, Jacquez J, Simon C, Foxman B, Pollock S, Barth-Jones D, Adams A, Welch G,
Lange K. 1997. The role of primary HIV infection in the spread of HIV through populations.
J
AIDS
14
:249-258.
131. Budd T. 2000.
Understanding object-oriented programming with Java
, 2nd ed. Addison-
Wesley, Reading, MA.
132. Resnick M. 1994.
Turtles, termites and traffic jams: explorations in massively parallel mi-
croworlds
. MIT Press, Cambridge.
133. Brown JS, Duguid P. 2000.
The social life of information
. Harvard Business School Press P,
Boston.
134. Bonabeau E, Dorigo M, Theraulaz G. 1999.
Swarm intelligence: from natural to artificial
systems
. Oxford UP, Oxford.
135. Lerman K.
Design and mathematical analysis of agent-based systems
. E-print, Information
Sciences Institute, University of Southern California, 2000 (http://www.isi.edu/~lerman/
papers/fmw00_abstract.html).
136. Ossowski S. 2000.
Co-ordination in artificial agent societies: social structure and its implica-
tions for autonomous problem-solving agents
. Springer, Berlin.
137. Wooldridge M. 2000.
Reasoning about rational agents
. MIT Press, Cambridge.
138. Jonker CM, Snoep JL, Treur J, Westerhoff HV, Wijngaards WAC. 2002. Putting intentions
into cell biochemistry: An artificial intelligence perspective.
J Theor Biol
214
:105-134.
139. Chaikin PM, Lubensky TC. 1995.
Principles of condensed matter physics
. Cambridge UP,
Cambridge.
140. Hammersley JM, Handscomb DC. 1964.
Monte Carlo methods
. Chapman and Hall, London.
141. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. 1953. Equations of state
calculations by fast computing machines.
J Chem Phys
21
:1087-1092.
142. Brémaud P. 1999.
Markov chains: gibbs fields, monte carlo simulation, and queues
. Springer,
Berlin.
143. Beckerman M. 1997.
Adaptive cooperative systems
. Wiley, New York.
144. Jordan MI, ed. 1998.
Learning in graphical models
. Kluwer Academic, Dordrecht.
145. Young HP. 1998.
Individual strategy and social structure: an evolutionary theory of institu-
tions
. Princeton UP, Princeton.
146. Sutton J. 1998.
Technology and market structure: theory and history
. MIT Press, Cambridge.