es.evaluate

For each element in solution 's' evaluate the respective
fitness.

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

es.evaluate function

<dl><dt>f</dt>
<dd>A reference to an instance of objective function</dd>
<dt>s</dt>
<dd>The set of solutions</dd>
<dt>enforce</dt>
<dd>If true the values are enforced to fall within provided range</dd></dl>

Arguments

es.evaluate — es.evaluate

<dl>

<dt>f</dt>
<dd>A reference to an instance of objective function</dd>


<dt>s</dt>
<dd>The set of solutions</dd>


<dt>enforce</dt>
<dd>If true the values are enforced to fall within provided range</dd>

</dl>

es.evaluate: es.evaluate

Description

Usage

Value

Arguments