ees1.explore

Explore the solution space on the neighborhood of
solution 's' in order to find a new best.

The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible
package providing optimization driven parameter estimation methods using metaheuristics and
evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization
for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require,
in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there
are built in support for models developed with 'Repast Simphony' Agent-Based framework (<https://repast.github.io/>)
and with NetLogo (<https://www.netlogo.org/>) which are the most used frameworks for Agent-based modeling.

Antonio Prestes Garcia

evoper

Evolutionary Parameter Estimation for 'Repast Simphony' Models

Alfonso  Rodriguez-Paton

ees1.explore function

<dl><dt>s</dt>
<dd>The Problem solution</dd>
<dt>weight</dt>
<dd>The exploration intensity</dd>
<dt>p</dt>
<dd>The mutation probability</dd></dl>

Arguments

ees1.explore — ees1.explore

<dl>

<dt>s</dt>
<dd>The Problem solution</dd>


<dt>weight</dt>
<dd>The exploration intensity</dd>


<dt>p</dt>
<dd>The mutation probability</dd>

</dl>

ees1.explore: ees1.explore

Description

Usage

Arguments