Documentation
¶
Index ¶
- Constants
- Variables
- type Inference
- type LogIteration
- type RangeFinder
- func (r *RangeFinder) AnalyzeInferences(detailed bool) string
- func (r *RangeFinder) BagMap() []uint8
- func (r *RangeFinder) ExhaustiveTotal() int
- func (r *RangeFinder) Infer(ctx context.Context) error
- func (r *RangeFinder) InferElapsed() time.Duration
- func (r *RangeFinder) Inferences() *Inference
- func (r *RangeFinder) Init(game *game.Game, eqCalcs []equity.EquityCalculator, cfg *config.Config)
- func (r *RangeFinder) IsBusy() bool
- func (r *RangeFinder) PrepareFinder(myRack []tilemapping.MachineLetter) error
- func (r *RangeFinder) Reset()
- func (r *RangeFinder) SetLogStream(l io.Writer)
- func (r *RangeFinder) SetMaxEnumeratedLeaves(n int)
- func (r *RangeFinder) SetSimIters(n int)
- func (r *RangeFinder) SetTau(tau float64)
- func (r *RangeFinder) SetThreads(t int)
- func (r *RangeFinder) SimCount() uint64
- func (r *RangeFinder) SimIters() int
- func (r *RangeFinder) Tau() float64
Constants ¶
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const ( // DefaultMaxEnumeratedLeaves is the default threshold for exhaustive enumeration. // When the number of distinct leaves drawable from the bag is at or below this // value, inferEnumerated is used instead of Monte Carlo sampling. // At ~100 ms per mini-sim and 16 threads this corresponds to roughly 30 s of wall // time, which is the natural knee of the tractability curve: // k=1 → ≤27 leaves (always enumerate) // k=2 → ≤378 leaves (always enumerate) // k=3 → ≤3650 leaves (enumerate when bag is modest, ≤~20 distinct tiles) // k=4 → ≤27000 leaves (enumerate only when bag ≤~15 tiles total) // Anything above 750 typically exceeds the default 1m sampling budget and won't // beat MC in practice. DefaultMaxEnumeratedLeaves = 750 )
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const ( // SoftmaxTemperature controls how "rational" we assume the opponent to be // when computing P(play | leave). Lower values assume near-optimal play; // higher values allow more weight for sub-optimal plays. // Softmax is applied over log-odds of win probabilities, so tau is on the // log-odds scale. Typical positions (20%-80% win prob) span roughly [-1.4, 1.4]; // strongly won/lost positions (5%-95%) reach about [-3, 3]. SoftmaxTemperature = 0.05 )
Variables ¶
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var ErrBagEmpty = errors.New("bag is empty")
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var ErrMoveTypeNotSupported = errors.New("opponent move type not suitable for inference")
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var ErrNoEvents = errors.New("no events")
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var ErrNoInformation = errors.New("not enough information to infer")
Functions ¶
This section is empty.
Types ¶
type Inference ¶ added in v0.10.2
type Inference struct {
RackLength int
InferredRacks []montecarlo.InferredRack
// contains filtered or unexported fields
}
func NewInference ¶ added in v0.10.2
func NewInference() *Inference
type LogIteration ¶
type LogIteration struct {
Iteration int `json:"iteration" yaml:"iteration"`
Thread int `json:"thread" yaml:"thread"`
Rack string `json:"rack" yaml:"rack"`
TopMoveWinProb float64 `json:"topMoveWinProb" yaml:"topMoveWinProb"`
TopMove string `json:"topMove" yaml:"topMove"`
// InferredMoveWinProb is the win prob of the move we are inferring, given
// that they drew "Rack"
InferredMoveWinProb float64 `json:"inferredMoveWinProb" yaml:"inferredMoveWinProb"`
// Likelihood = softmax P(play|leave) with temperature tau
Likelihood float64 `json:"likelihood" yaml:"likelihood"`
SimLogFile string `json:"simLogFile,omitempty" yaml:"simLogFile,omitempty"`
}
type RangeFinder ¶
type RangeFinder struct {
// contains filtered or unexported fields
}
func (*RangeFinder) AnalyzeInferences ¶
func (r *RangeFinder) AnalyzeInferences(detailed bool) string
func (*RangeFinder) BagMap ¶ added in v0.13.0
func (r *RangeFinder) BagMap() []uint8
BagMap returns a copy of the inferenceBagMap after PrepareFinder has been called. It represents the pool of tiles from which the opponent's leave was drawn (bag + both racks, minus opp's played tiles this turn).
func (*RangeFinder) ExhaustiveTotal ¶ added in v0.13.0
func (r *RangeFinder) ExhaustiveTotal() int
ExhaustiveTotal returns the total number of distinct leaves that existed when inferEnumerated was used. Zero means the MC sampling path was taken.
func (*RangeFinder) InferElapsed ¶ added in v0.13.0
func (r *RangeFinder) InferElapsed() time.Duration
InferElapsed returns the wall-clock duration of the last Infer call.
func (*RangeFinder) Inferences ¶
func (r *RangeFinder) Inferences() *Inference
func (*RangeFinder) Init ¶
func (r *RangeFinder) Init(game *game.Game, eqCalcs []equity.EquityCalculator, cfg *config.Config)
func (*RangeFinder) IsBusy ¶ added in v0.8.6
func (r *RangeFinder) IsBusy() bool
func (*RangeFinder) PrepareFinder ¶
func (r *RangeFinder) PrepareFinder(myRack []tilemapping.MachineLetter) error
func (*RangeFinder) Reset ¶
func (r *RangeFinder) Reset()
func (*RangeFinder) SetLogStream ¶
func (r *RangeFinder) SetLogStream(l io.Writer)
func (*RangeFinder) SetMaxEnumeratedLeaves ¶ added in v0.13.0
func (r *RangeFinder) SetMaxEnumeratedLeaves(n int)
SetMaxEnumeratedLeaves sets the maximum number of distinct leaves for which exhaustive enumeration (inferEnumerated) is used instead of Monte Carlo sampling. If 0, DefaultMaxEnumeratedLeaves is used.
func (*RangeFinder) SetSimIters ¶ added in v0.13.0
func (r *RangeFinder) SetSimIters(n int)
func (*RangeFinder) SetTau ¶ added in v0.13.0
func (r *RangeFinder) SetTau(tau float64)
SetTau sets the softmax temperature for P(play | leave). Lower values assume the opponent plays more optimally; higher values give more weight to sub-optimal plays. Must be called before PrepareFinder.
func (*RangeFinder) SetThreads ¶
func (r *RangeFinder) SetThreads(t int)
func (*RangeFinder) SimCount ¶ added in v0.13.0
func (r *RangeFinder) SimCount() uint64
SimCount returns the total number of mini-simulations run during Infer.
func (*RangeFinder) SimIters ¶ added in v0.13.0
func (r *RangeFinder) SimIters() int
func (*RangeFinder) Tau ¶ added in v0.13.0
func (r *RangeFinder) Tau() float64
Source Files
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