| –minibatch-size | MinibatchSize | How many positions the engine tries to batch together for parallel NN computation. Larger batches may reduce strength a bit, especially with a small number of playouts.Default value: 256 Minimum value: 1 Maximum value: 1024 |
| –max-prefetch | MaxPrefetch | When the engine cannot gather a large enough batch for immediate use, try to prefetch up to X positions which are likely to be useful soon, and put them into cache.Default value: 32 Minimum value: 0 Maximum value: 1024 |
| –cpuct | CPuct | cpuct_init constant from “UCT search” algorithm. Higher values promote more exploration/wider search, lower values promote more confidence/deeper search.Default value: 3.00 Minimum value: 0.00 Maximum value: 100.00 |
| –cpuct-base | CPuctBase | cpuct_base constant from “UCT search” algorithm. Lower value means higher growth of Cpuct as number of node visits grows.Default value: 19652.00 Minimum value: 1.00 Maximum value: 1000000000.00 |
| –cpuct-factor | CPuctFactor | Multiplier for the cpuct growth formula.Default value: 2.00 Minimum value: 0.00 Maximum value: 1000.00 |
| –temperature | Temperature | Tau value from softmax formula for the first move. If equal to 0, the engine picks the best move to make. Larger values increase randomness while making the move.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00 |
| –tempdecay-moves | TempDecayMoves | Reduce temperature for every move from the game start to this number of moves, decreasing linearly from initial temperature to 0. A value of 0 disables tempdecay.Default value: 0 Minimum value: 0 Maximum value: 100 |
| –temp-cutoff-move | TempCutoffMove | Move number, starting from which endgame temperature is used rather than initial temperature. Setting it to 0 disables cutoff.Default value: 0 Minimum value: 0 Maximum value: 1000 |
| –temp-endgame | TempEndgame | Temperature used during endgame (starting from cutoff move). Endgame temperature doesn’t decay.Default value: 0.00 Minimum value: 0.00 Maximum value: 100.00 |
| –temp-value-cutoff | TempValueCutoff | When move is selected using temperature, bad moves (with win probability less than X than the best move) are not considered at all.Default value: 100.00 Minimum value: 0.00 Maximum value: 100.00 |
| –temp-visit-offset | TempVisitOffset | Reduces visits by this value when picking a move with a temperature. When the offset is less than number of visits for a particular move, that move is not picked at all.Default value: 0.00 Minimum value: -1.00 Maximum value: 1000.00 |
| –noise, -n | DirichletNoise | Add Dirichlet noise to root node prior probabilities. This allows the engine to discover new ideas during training by exploring moves which are known to be bad. Not normally used during play.Default value: false |
| –verbose-move-stats | VerboseMoveStats | Display Q, V, N, U and P values of every move candidate after each move.Default value: false |
| –smart-pruning-factor | SmartPruningFactor | Do not spend time on the moves which cannot become bestmove given the remaining time to search. When no other move can overtake the current best, the search stops, saving the time. Values greater than 1 stop less promising moves from being considered even earlier. Values less than 1 causes hopeless moves to still have some attention. When set to 0, smart pruning is deactivated.Default value: 1.33 Minimum value: 0.00 Maximum value: 10.00 |
| –fpu-strategy | FpuStrategy | How is an eval of unvisited node determined. “reduction” subtracts --fpu-reduction value from the parent eval. “absolute” sets eval of unvisited nodes to the value specified in --fpu-value.Default value: reduction Allowed values: reduction, absolute |
| –fpu-reduction | FpuReduction | “First Play Urgency” reduction (used when FPU strategy is “reduction”). Normally when a move has no visits, it’s eval is assumed to be equal to parent’s eval. With non-zero FPU reduction, eval of unvisited move is decreased by that value, discouraging visits of unvisited moves, and saving those visits for (hopefully) more promising moves.Default value: 1.20 Minimum value: -100.00 Maximum value: 100.00 |
| –fpu-value | FpuValue | “First Play Urgency” value. When FPU strategy is “absolute”, value of unvisited node is assumed to be equal to this value, and does not depend on parent eval.Default value: -1.00 Minimum value: -1.00 Maximum value: 1.00 |
| –cache-history-length | CacheHistoryLength | Length of history, in half-moves, to include into the cache key. When this value is less than history that NN uses to eval a position, it’s possble that the search will use eval of the same position with different history taken from cache.Default value: 0 Minimum value: 0 Maximum value: 7 |
| –policy-softmax-temp | PolicyTemperature | Policy softmax temperature. Higher values make priors of move candidates closer to each other, widening the search.Default value: 2.20 Minimum value: 0.10 Maximum value: 10.00 |
| –max-collision-events | MaxCollisionEvents | Allowed node collision events, per batch.Default value: 32 Minimum value: 1 Maximum value: 1024 |
| –max-collision-visits | MaxCollisionVisits | Total allowed node collision visits, per batch.Default value: 9999 Minimum value: 1 Maximum value: 1000000 |
| –out-of-order-eval | OutOfOrderEval | During the gathering of a batch for NN to eval, if position happens to be in the cache or is terminal, evaluate it right away without sending the batch to the NN. When off, this may only happen with the very first node of a batch; when on, this can happen with any node.Default value: true |
| –syzygy-fast-play | SyzygyFastPlay | With DTZ tablebase files, only allow the network pick from winning moves that have shortest DTZ to play faster (but not necessarily optimally).Default value: true |
| –multipv | MultiPV | Number of game play lines (principal variations) to show in UCI info output.Default value: 1 Minimum value: 1 Maximum value: 500 |
| –score-type | ScoreType | What to display as score. Either centipawns (the UCI default), win percentage or Q (the actual internal score) multiplied by 100.Default value: centipawn Allowed values: centipawn, win_percentage, Q |
| –history-fill | HistoryFill | Neural network uses 7 previous board positions in addition to the current one. During the first moves of the game such historical positions don’t exist, but they can be synthesized. This parameter defines when to synthesize them (always, never, or only at non-standard fen position).Default value: fen_only Allowed values: no, fen_only, always |
| –kldgain-average-interval | KLDGainAverageInterval | Used to decide how frequently to evaluate the average KLDGainPerNode to check the MinimumKLDGainPerNode, if specified.Default value: 100 Minimum value: 1 Maximum value: 10000000 |
| –minimum-kldgain-per-node | MinimumKLDGainPerNode | If greater than 0 search will abort unless the last KLDGainAverageInterval nodes have an average gain per node of at least this much.Default value: 0.00 Minimum value: 0.00 Maximum value: 1.00 |
