Yousf alrukh (30 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neuware - Goal Management for Autonomous Software is a guide to treating goals as first-class runtime objects: what they are, how they compete for attention and resources, how their progress is tracked and verified, and how they adapt when the world changes underneath them. Eleven chapters cover the full goal management stack: - Goals as runtime objects: explicit states, independently checkable success criteria, continuous constraints, traceable ownership- Goal graphs and dependencies: prerequisites, meaningfully-grained subgoals, branching, traversal-based completion- Priority arbitration: separated urgency and importance, policy-driven ratings, resource cost, conflict detection- Progress tracking: milestones, independently verifiable evidence, a status model that can represent regression, stall detection- Dynamic replanning: specific triggers, scope-matched failure response, constraint re-validation, conservative fallbacks- Resource-aware goal scheduling: enforced budgets, concurrency limits, dynamic capacity, deadline slack tracking- Goal verification: validated success checks, graded completion, honest confidence, downstream-aware rollback- Human override and escalation: logged reprioritization, scoped exceptions, informative approval gates, reconciled termination- Failure modes in goal management: goal loops, priority inversion, drift, unbounded expansion- Production goal engines: transactional persistence, reconstruction-oriented auditing, population-level observability>Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a goal management maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building autonomous systems, planning engines, and any software where goals compete for attention and resources without constant human direction.…

Taschenbuch. Zustand: Neu. Neuware - Event-Driven Agent Networks is a practical systems-oriented guide to building, coordinating, and operating distributed agent systems.The book explores the engineering principles behind event buses, agent messaging, coordination protocols, distributed task execution, state and event consistency, resilience, backpressure, cross-agent context exchange, security, observability, and operational management.Designed for readers interested in modern agent infrastructure and distributed software systems, this guide focuses on measurable engineering practices, explicit assumptions, reproducible validation, failure handling, and operational reliability.Throughout the book, concepts are connected to practical engineering decisions, helping readers understand how distributed agents communicate, coordinate work, exchange context, maintain consistent state, and recover from failures.Whether you are exploring agentic systems, distributed architectures, or event-driven software, Event-Driven Agent Networks provides a structured technical reference for understanding the components and practices required to build reliable multi-agent infrastructure.…

Taschenbuch. Zustand: Neu. Neuware - AI Agent Memory Systems is a guide to designing what an agent remembers, for how long, and how it finds what it remembers when it needs it. Memory is the subsystem that lets an agent's behavior improve across interactions rather than starting fresh every time - and it is also where privacy risk, staleness, and quiet corruption most often accumulate. Eleven chapters cover the full memory stack: - Memory as an agent subsystem: distinct memory roles, state boundaries, lifecycle, and architectural privacy- Short-term context management: working context, turn history, context budgets, recency weighting- Long-term memory architecture: persistent stores, episodic memory, semantic memory, profiles- Retrieval for agent memory: embedding search, metadata filters, ranking, freshness- Summarization and compression: memory summaries, fact extraction, context compression, loss control- Memory write policies: salience, deduplication, confidence, retention- Memory consistency and updating: conflict resolution, staleness, revision, deletion- Privacy and access control: sensitive data classification, permissions, retention limits, auditability- Memory evaluation: retrieval quality, factual persistence, contamination testing, behavior impact- Production memory operations: monitoring, migration, backups, continuous tuning>Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a memory maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building AI agents, copilots, and any system where persistent memory shapes user-facing behavior. …

Taschenbuch. Zustand: Neu. Neuware - AI Tool-Use Engineering is a guide to the interface between a language model's reasoning and the systems it can actually affect: function calling, tool routing, permission boundaries, execution control, and verification. This is the layer where a model's decision to act becomes a real action with real consequences. Eleven chapters cover the full tool-use stack: - Tool-using AI architecture: tool catalog design, schemas, routing, and a separated execution layer- Function calling interfaces: typed arguments, interface-level validation, typed outputs, actionable error surfaces- Tool routing and selection: intent mapping, capability boundaries, cost-aware routing, fallback chains- Permission boundaries: scopes, least privilege, execution-layer-only credentials, informative approval gates- Execution control: tool-specific timeouts, layered resource limits, runtime-enforced sandboxing, clean cancellation- Result verification: automatic schema checks, genuinely independent cross-validation, confirmed side effects- Reliable multi-step tool workflows: externally tracked state, explicit dependencies, step-level retry, compensation- Security and abuse resistance: injection defense, misuse detection, exfiltration prevention, execution-layer policy- Testing tool-using systems: deterministic mocks, failure injection, decision-path coverage, regression triggers- Production tool infrastructure: a single tool registry, explicit versioning, decision-inclusive observability>Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a tool-use maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building AI agents, copilots, and any system where a model's decisions translate into real actions.…

Taschenbuch. Zustand: Neu. Neuware.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.