... Artificial societies
Simulation techniques, tools and environments
... Population dynamics: Does not (really) relate to micro behaviour
Physics-derived models: Can be useful for post hoc encapsulation
Descriptive computational simulation: difficult to get enough observations
Computational Sociology and Agent-Based Modeling
... hierarchical system of institutions and norms that shape
individual behavior from the top down
• Growing interest in the possibility that human groups may
be highly complex, non-linear, path-dependent, and selforganizing
• To understand these dynamics much better … by trying to model
... • ”the agent-oriented philosophy for dealing
with organisational relationships is
appropriate for complex systems”
Agent-based systems flexibly form and reshape
Individual agents or groups can be developed
separately and incrementally added to the system
Initial Draft: Related Works Section
... implement distributed diffusion and distributed aggregation. Mobile agent based directed
diffusion in wireless sensor networks is discussed in .
slides - NIMML
... – finite set
– continuous or discrete
Modeling 101. Different Types of Models Designed for Different Uses
... Agent-based models (ABMs) are also dynamic models that simulate the behavior of a system
over time. However, they take a bottom-up, or individual-level, approach, specifying the rules
that govern the behavior of individuals and allowing the overall behavior of the system to
emerge from the interacti ...
Yuan - GeoSpatial and GeoTemporal Informatics
... What is missing (discuss areas not
currently on the radar)
• From space-time observations to spatiotemporal processes
• Informatics framework to automate recognition of events and
• Analysis of events and processes
– Weather (obs > events > systems > severity)
– Population (obs > migratio ...
... • Bounded rationality: essentially impossible to give
agents full rationality in non-trivial environments
• ‘Local’ interactions: agent-agent interactions
mediated by inhomogeneous topology (e.g., graph,
social network, space)
• Focus on dynamics: paths to equilibrium and nonequilibrium processes
P2P Distributed Artificial Intelligence
... Possible Economic Models (1)
• Secrecy: agents keep some part of their internal state
• Money: forwading and task completion means money
income, agents try to increase their wealth
• Added value: wealth coming from outside of the system
• Discounts: forwarders of large amounts get lower pric ...
agent cultures and zombielands. fields, fictions and futures of agent
... Sara Del Valle is a scientist at Los Alamos National Laboratory. She is a mathematician and obtained her PhD from
the University of Iowa in 2003 in Applied Mathematics and Computational Sciences. She has worked extensively on
mathematical and computational epidemiology. Her research focuses on impro ...
Agent Design for Agent-Based Modelling
... Architectures with associated condition-action rules (1) can be very simple – no more
that a couple of variables and a handful of (possibly fuzzy) rules – or can be highly
complex and support advanced cognitive processes. Artificial neural networks (2)
take as their building blocks simple computatio ...
notes - School of Computer Science and Statistics
... • “(...) an example of how simple agents acting only on local information
can produce complex global behaviour”.
• Agents: HeatBugs which absorb and expel heat
• Model: HeatBugsModel has a spatial property, heat, which diffuses and
evaporates over time. (green dots represent HeatBugs, brighter red r ...
MyBio - Purdue University
... equations, etc. Also, the multidimensional version of the algorithm could be applied for solving these
PDE like the Hamilton-Jacobi-Bellman PDE (in optimal feedback control), the Hamilton-Jacobi-Isaacs
PDE (in dynamic games and reachability analysis for hybrid control systems).
Agent-oriented Engineering of Trust Management Systems
... multiagent systems consisting of just software agents, we focus on sociotechnical
systems, where each software agent is paired with it principal participating in
a social network. For achieving the goals set for a sociotechnical system, agents
interact and exchange knowledge. As socio-technical syst ...
complex social system
... Infectious (I): Infected Individuals able to transmit the parasite to others
Recovered (R): Individuals that have recovered, are immune or have died
from the disease and do not contribute to the transmission of the disease
Parameters: α, β
Variables: S, I, R
Project Specification LDR - IEI: Linköping University
... current shop floors has led to the emergence of several models/architectures for fully autonomous
operation of plants. These models build on state of the art research combining artificial intelligence
with distributed computing and production. Autonomy in this context implies that stations, buffers, ...
... It is useful when the ascription helps us to understand the structure of the machine,
its past or future behaviour, or how to repair or improve it.
It is perhaps never logically required even for humans, but expressing reasonably
briefly what is actually known about the state of the machine in a par ...
Engineering Good-Enough Social Interaction
... The spontaneous developments of the Web 2.0 taught us how unexpected, rich and
widespread new practices and forms of social coordination may be. Applications like
the Wikipedia and Facebook illustrate how significant is the role of a computational
and social “backdrop” to enable that coordination an ...
An agent-based model (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo Methods are used to introduce randomness. Particularly within ecology, ABMs are also called individual-based models (IBMs), and individuals within IBMs may be simpler than fully autonomous agents within ABMs. A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used on non-computing related scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.Agent-based models are a kind of microscale model that simulate the simultaneous operations and interactions of multiple agents in an attempt to re-create and predict the appearance of complex phenomena. The process is one of emergence from the lower (micro) level of systems to a higher (macro) level. As such, a key notion is that simple behavioral rules generate complex behavior. This principle, known as K.I.S.S. (""Keep it simple, stupid"") is extensively adopted in the modeling community. Another central tenet is that the whole is greater than the sum of the parts. Individual agents are typically characterized as boundedly rational, presumed to be acting in what they perceive as their own interests, such as reproduction, economic benefit, or social status, using heuristics or simple decision-making rules. ABM agents may experience ""learning"", adaptation, and reproduction.Most agent-based models are composed of: (1) numerous agents specified at various scales (typically referred to as agent-granularity); (2) decision-making heuristics; (3) learning rules or adaptive processes; (4) an interaction topology; and (5) a non-agent environment. ABMs are typically implemented as computer simulations, either as custom software, or via ABM toolkits, and this software can be then used to test how changes in individual behaviors will affect the system's emerging overall behavior.