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Documentation
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Overview ¶
The maze solving experiments based on NEAT methodology with Novelty Search and Fitness based optimization
Index ¶
Constants ¶
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Variables ¶
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Functions ¶
This section is empty.
Types ¶
type Agent ¶
type Agent struct {
// The current location
Location Point
// The heading direction in degrees
Heading float64
// The speed of agent
Speed float64
// The angular velocity
AngularVelocity float64
// The radius of agent body
Radius float64
// The maximal range of range finder sensors
RangeFinderRange float64
// The angles of range finder sensors
RangeFinderAngles []float64
// The beginning angles for radar sensors
RadarAngles1 []float64
// The ending angles for radar sensors
RadarAngles2 []float64
// stores radar outputs
Radar []float64
// stores rangefinder outputs
RangeFinders []float64
}
The class for the maze navigator agent
type AgentRecord ¶
type AgentRecord struct {
// The ID of agent
AgentID int
// The agent position at the end of simulation
X, Y float64
// The agent fitness
Fitness float64
// The flag to indicate whether agent reached maze exit
GotExit bool
// The population generation when agent data was collected
Generation int
// The novelty value associated
Novelty float64
// The ID of species to whom individual belongs
SpeciesID int
// The age of species to whom individual belongs at time of recording
SpeciesAge int
}
The record holding info about individual maze agent performance at the end of simulation
type Environment ¶
type Environment struct {
// The maze navigating agent
Hero Agent
// The maze line segments
Lines []Line
// The maze exit - goal
MazeExit Point
// The flag to indicate if exit was found
ExitFound bool
// The number of time steps to be executed during maze solving simulation
TimeSteps int
// The sample step size to determine when to collect subsequent samples during simulation
SampleSize int
// The range around maze exit point to test if agent coordinates is within to be considered as solved successfully (5.0 is good enough)
ExitFoundRange float64
// contains filtered or unexported fields
}
The maze environment class
func ReadEnvironment ¶
func ReadEnvironment(ir io.Reader) (*Environment, error)
Reads maze environment from reader
func (*Environment) AgentDistanceToExit ¶
func (e *Environment) AgentDistanceToExit() float64
used for fitness calculations based on distance of maze Agent to the target maze exit
func (*Environment) ApplyOutputs ¶
func (e *Environment) ApplyOutputs(o1, o2 float64) error
transform neural net outputs into angular velocity and speed
func (*Environment) GetInputs ¶
func (e *Environment) GetInputs() ([]float64, error)
create neural net inputs from maze agent sensors
func (*Environment) Update ¶
func (e *Environment) Update() error
Do one time step of the simulation
type Line ¶
type Line struct {
A, B Point
}
The simple line segment class, used for maze walls
func (Line) Intersection ¶
Returns point of intersection between two line segments if it exists
type MazeNoveltySearchEvaluator ¶
type MazeNoveltySearchEvaluator struct {
// The output path to store execution results
OutputPath string
// The maze seed environment
Environment *Environment
// The target number of species to be maintained
NumSpeciesTarget int
// The species compatibility threshold adjustment frequency
CompatAdjustFreq int
}
The maze solving experiment with Novelty Search optimization of NEAT algorithm
func (MazeNoveltySearchEvaluator) GenerationEvaluate ¶
func (e MazeNoveltySearchEvaluator) GenerationEvaluate(pop *genetics.Population, epoch *experiments.Generation, context *neat.NeatContext) (err error)
This method evaluates one epoch for given population and prints results into output directory if any.
func (MazeNoveltySearchEvaluator) TrialRunStarted ¶
func (e MazeNoveltySearchEvaluator) TrialRunStarted(trial *experiments.Trial)
Invoked before new trial run started
type MazeObjectiveEvaluator ¶
type MazeObjectiveEvaluator struct {
// The output path to store execution results
OutputPath string
// The maze seed environment
Environment *Environment
// The target number of species to be maintained
NumSpeciesTarget int
// The species compatibility threshold adjustment frequency
CompatAdjustFreq int
}
The maze solving experiment with objective fitness-based optimization of NEAT algorithm
func (MazeObjectiveEvaluator) GenerationEvaluate ¶
func (e MazeObjectiveEvaluator) GenerationEvaluate(pop *genetics.Population, epoch *experiments.Generation, context *neat.NeatContext) (err error)
This method evaluates one epoch for given population and prints results into output directory if any.
func (MazeObjectiveEvaluator) TrialRunStarted ¶
func (e MazeObjectiveEvaluator) TrialRunStarted(trial *experiments.Trial)
Invoked before new trial run started
type Point ¶
type Point struct {
X, Y float64
}
The simple point class
func (Point) Angle ¶
To determine angle in degrees of vector defined by (0,0)->This Point. The angle is from 0 to 360 degrees anti clockwise.
type RecordStore ¶
type RecordStore struct {
// The array of agent records
Records []AgentRecord
// The array of the solver agent path points
SolverPathPoints []Point
}
The maze agent records storage
Source Files